31 Kaldi Jobs

Redefine the future of customer experiences. One conversation at a time. We're changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you're ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you're in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing Nextiva, a leader in business communications, is seeking a skilled AI Technical Lead to join our AI Agents team within our Data & Intelligence Platform group. In this role, you will develop intelligent, multimodal AI agents (voice and chatbots) as part of Nextiva's next-generation customer experience platform. You will apply expertise in machine learning and software engineering to build AI-driven features that transform how businesses engage with customers. This position offers the opportunity to work at the forefront of generative AI and multimodal interactions, creating scalable AI solutions that blend automation with the human touch to deliver exceptional customer experiences. The Technical Lead is a senior individual contributor who combines deep technical expertise with hands-on execution. They actively write code, take ownership of end-to-end feature delivery, and are involved in architectural and design discussions. They also conduct code reviews, mentor engineers, and collaborate closely with cross-functional teams to deliver scalable, high-quality solutions aligned with the product vision and goals. As a key technical leader within the team, this role offers a strong pathway for professional growth, whether deepening expertise as a highly skilled individual contributor or evolving into engineering management. Key Responsibilities: Design & Develop AI Agents: Design, implement, and refine AI agents for Nextiva's products that understand and respond to customers in multiple formats (e.g., spoken voice, written text). Develop conversational logic and multimodal interaction flows leveraging state-of-the-art natural language processing (NLP) and speech recognition techniques. AI Model Integration: Integrate large language models and other AI/ML components into the Agentic AI Platform to enable capabilities such as question answering, task automation, sentiment analysis, and recommendations. Ensure that AI models and solutions perform effectively in real-world environments and at scale. Full Lifecycle Engineering: Own the end-to-end development lifecycle of AI features. Multimodal Interaction Systems: Build and integrate components for multimodal interactions, including speech-to-text, text-to-speech, and dialog management systems. Performance Optimization: Optimize AI algorithms and agent frameworks for performance, scalability, and reliability. Use data-driven methods to tune model accuracy and response times. Quality, Ethics & Compliance: Implement robust testing (unit, integration, end-to-end) for AI features to ensure reliability and correctness. Incorporate ethical AI practices, ensuring AI agent behavior is unbiased and compliant with privacy and security regulations. Documentation & Mentorship: Document AI agent designs, algorithms, and usage guidelines for future reference. Provide technical guidance and mentorship to junior engineers or new team members as needed. Success in this role will be measured by your ability to deliver AI features that measurably improve customer experiences (e.g., higher self-service resolution rates, faster response times, improved user satisfaction) while maintaining high software quality and ethical AI standards. You will help Nextiva achieve a balanced integration of AI and human interaction, directly contributing to our CX-first vision. Qualifications Education: Bachelor's degree in computer science, Software Engineering, or a related field (required). A Master's degree in AI, Machine Learning, or a related discipline is strongly preferred. Equivalent practical experience in AI/ML development will also be considered. Software Engineering Experience: 8+ years of professional software development experience, including at least 5+ years building AI or machine-learning powered applications. Proven experience developing production-grade software (e.g., backend services, APIs, data pipelines) in a collaborative team environment. AI/ML Expertise: Strong understanding of AI and machine learning fundamentals with hands-on experience in natural language processing (NLP) and/or deep learning. Familiarity with the latest AI advancements (e.g., transformer-based models, conversational AI frameworks) and a history of applying AI models to solve real-world problems. Technical Skills: Proficiency in programming languages commonly used for AI development, such as Python (with ML libraries like TensorFlow or PyTorch) and/or a general-purpose language like Java or C# for scalable systems. Experience with machine learning frameworks and libraries for NLP, speech, or computer vision (e.g., Hugging Face Transformers, OpenAI APIs, spaCy, Kaldi, AWS/GCP/Azure AI services) is expected. Multimodal Interaction Knowledge: Experience with speech and language technologies – for example, integrating speech-to-text (ASR) and text-to-speech (TTS) engines, or building chatbots and voice bots for conversational interfaces. Cloud & Scalability: Familiarity with cloud platforms and deploying AI/ML models at scale (AWS, Google Cloud, or Azure). Experience with microservices architecture and containerization (Docker, Kubernetes) for AI services. Collaboration & Communication: Excellent teamwork and communication skills. Nextiva DNA (Core Competencies) Nextiva's most successful team members share common traits and behaviors: Drives Results: Action-oriented with a passion for solving problems. They bring clarity and simplicity to ambiguous situations, challenge the status quo, and ask what can be done differently. They lead and drive change, celebrating success to build more success. Critical Thinker: Understands the "why" and identifies key drivers, learning from the past. They are fact-based and data-driven, forward-thinking , and see problems a few steps ahead. They provide options, recommendations, and actions, understanding risks and dependencies. Right Attitude : They are team-oriented, collaborative, competitive, and hate losing. They are resilient, able to bounce back from setbacks, zoom in and out, and get in the trenches to help solve important problems. They cultivate a culture of service, learning, support, and respect, caring for customers and teams. Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security - Provident Fund & Gratuity Wellness ‍ - Employee Assistance Program and comprehensive wellness initiatives Growth - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what's going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog. #LI-PJ1 #LI-Hybrid

Redefine the future of customer experiences. One conversation at a time. We’re changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you’re ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you’re in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing Nextiva, a leader in business communications, is seeking a skilled AI Technical Lead to join our AI Agents team within our Data & Intelligence Platform group. In this role, you will develop intelligent, multimodal AI agents (voice and chatbots) as part of Nextiva’s next-generation customer experience platform. You will apply expertise in machine learning and software engineering to build AI-driven features that transform how businesses engage with customers. This position offers the opportunity to work at the forefront of generative AI and multimodal interactions, creating scalable AI solutions that blend automation with the human touch to deliver exceptional customer experiences. The Technical Lead is a senior individual contributor who combines deep technical expertise with hands-on execution. They actively write code, take ownership of end-to-end feature delivery, and are involved in architectural and design discussions. They also conduct code reviews, mentor engineers, and collaborate closely with cross-functional teams to deliver scalable, high-quality solutions aligned with the product vision and goals. As a key technical leader within the team, this role offers a strong pathway for professional growth, whether deepening expertise as a highly skilled individual contributor or evolving into engineering management. Key Responsibilities Design & Develop AI Agents: Design, implement, and refine AI agents for Nextiva’s products that understand and respond to customers in multiple formats (e.g., spoken voice, written text). Develop conversational logic and multimodal interaction flows leveraging state-of-the-art natural language processing (NLP) and speech recognition techniques. AI Model Integration: Integrate large language models and other AI/ML components into the Agentic AI Platform to enable capabilities such as question answering, task automation, sentiment analysis, and recommendations. Ensure that AI models and solutions perform effectively in real-world environments and at scale. Full Lifecycle Engineering: Own the end-to-end development lifecycle of AI features. Multimodal Interaction Systems: Build and integrate components for multimodal interactions, including speech-to-text, text-to-speech, and dialog management systems. Performance Optimization: Optimize AI algorithms and agent frameworks for performance, scalability, and reliability. Use data-driven methods to tune model accuracy and response times. Quality, Ethics & Compliance: Implement robust testing (unit, integration, end-to-end) for AI features to ensure reliability and correctness. Incorporate ethical AI practices, ensuring AI agent behavior is unbiased and compliant with privacy and security regulations. Documentation & Mentorship: Document AI agent designs, algorithms, and usage guidelines for future reference. Provide technical guidance and mentorship to junior engineers or new team members as needed. Success in this role will be measured by your ability to deliver AI features that measurably improve customer experiences (e.g., higher self-service resolution rates, faster response times, improved user satisfaction) while maintaining high software quality and ethical AI standards. You will help Nextiva achieve a balanced integration of AI and human interaction, directly contributing to our CX-first vision. Qualifications Education: Bachelor’s degree in computer science, Software Engineering, or a related field (required). A Master’s degree in AI, Machine Learning, or a related discipline is strongly preferred. Equivalent practical experience in AI/ML development will also be considered. Software Engineering Experience: 8+ years of professional software development experience, including at least 5+ years building AI or machine-learning powered applications. Proven experience developing production-grade software (e.g., backend services, APIs, data pipelines) in a collaborative team environment. AI/ML Expertise: Strong understanding of AI and machine learning fundamentals with hands-on experience in natural language processing (NLP) and/or deep learning. Familiarity with the latest AI advancements (e.g., transformer-based models, conversational AI frameworks) and a history of applying AI models to solve real-world problems. Technical Skills: Proficiency in programming languages commonly used for AI development, such as Python (with ML libraries like TensorFlow or PyTorch) and/or a general-purpose language like Java or C# for scalable systems. Experience with machine learning frameworks and libraries for NLP, speech, or computer vision (e.g., Hugging Face Transformers, OpenAI APIs, spaCy, Kaldi, AWS/GCP/Azure AI services) is expected. Multimodal Interaction Knowledge: Experience with speech and language technologies – for example, integrating speech-to-text (ASR) and text-to-speech (TTS) engines, or building chatbots and voice bots for conversational interfaces. Cloud & Scalability: Familiarity with cloud platforms and deploying AI/ML models at scale (AWS, Google Cloud, or Azure). Experience with microservices architecture and containerization (Docker, Kubernetes) for AI services. Collaboration & Communication: Excellent teamwork and communication skills. Nextiva DNA (Core Competencies) Nextiva’s most successful team members share common traits and behaviors: Drives Results: Action-oriented with a passion for solving problems. They bring clarity and simplicity to ambiguous situations, challenge the status quo, and ask what can be done differently. They lead and drive change, celebrating success to build more success. Critical Thinker: Understands the "why" and identifies key drivers, learning from the past. They are fact-based and data-driven, forward-thinking, and see problems a few steps ahead. They provide options, recommendations, and actions, understanding risks and dependencies. Right Attitude: They are team-oriented, collaborative, competitive, and hate losing. They are resilient, able to bounce back from setbacks, zoom in and out, and get in the trenches to help solve important problems. They cultivate a culture of service, learning, support, and respect, caring for customers and teams. Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical 🩺 - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance 💼 - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ⚖️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security💰 - Provident Fund & Gratuity Wellness 🤸‍ - Employee Assistance Program and comprehensive wellness initiatives Growth 🌱 - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what’s going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog.

Job description 🚀 Job Title: AI Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 2-6 Years Level : Senior Level 🌐 About Darwix AI Darwix AI is one of India’s fastest-growing GenAI startups, revolutionizing the future of enterprise sales and customer engagement with real-time conversational intelligence. We are building a GenAI-powered agent-assist and pitch intelligence suite that captures, analyzes, and enhances every customer interaction—across voice, video, and chat—in real time. We serve leading enterprise clients across India, the UAE, and Southeast Asia and are backed by global VCs, top operators from Google, Salesforce, and McKinsey, and CXOs from the industry. This is your opportunity to join a high-caliber founding tech team solving frontier problems in real-time voice AI, multilingual transcription, retrieval-augmented generation (RAG), and fine-tuned LLMs at scale. 🧠 Role Overview As the AI Engineer , you will drive the development, deployment, and optimization of AI systems that power Darwix AI's real-time conversation intelligence platform. This includes voice-to-text transcription, speaker diarization, GenAI summarization, prompt engineering, knowledge retrieval, and real-time nudge delivery. You will lead a team of AI engineers and work closely with product managers, software architects, and data teams to ensure technical excellence, scalable architecture, and rapid iteration cycles. This is a high-ownership, hands-on leadership role where you will code, architect, and lead simultaneously. 🔧 Key Responsibilities 1. AI Architecture & Model Development Architect end-to-end AI pipelines for transcription, real-time inference, LLM integration, and vector-based retrieval. Build, fine-tune, and deploy STT models (Whisper, Wav2Vec2.0) and diarization systems for speaker separation. Implement GenAI pipelines using OpenAI, Gemini, LLaMA, Mistral, and other LLM APIs or open-source models. 2. Real-Time Voice AI System Development Design low-latency pipelines for capturing and processing audio in real-time across multi-lingual environments. Work on WebSocket-based bi-directional audio streaming, chunked inference, and result caching. Develop asynchronous, event-driven architectures for voice processing and decision-making. 3. RAG & Knowledge Graph Pipelines Create retrieval-augmented generation (RAG) systems that pull from structured and unstructured knowledge bases. Build vector DB architectures (e.g., FAISS, Pinecone, Weaviate) and connect to LangChain/LlamaIndex workflows. Own chunking, indexing, and embedding strategies (OpenAI, Cohere, Hugging Face embeddings). 4. Fine-Tuning & Prompt Engineering Fine-tune LLMs and foundational models using RLHF, SFT, PEFT (e.g., LoRA) as needed. Optimize prompts for summarization, categorization, tone analysis, objection handling, etc. Perform few-shot and zero-shot evaluations for quality benchmarking. 5. Pipeline Optimization & MLOps Ensure high availability and robustness of AI pipelines using CI/CD tools, Docker, Kubernetes, and GitHub Actions. Work with data engineering to streamline data ingestion, labeling, augmentation, and evaluation. Build internal tools to benchmark latency, accuracy, and relevance for production-grade AI features. 6. Team Leadership & Cross-Functional Collaboration Lead, mentor, and grow a high-performing AI engineering team. Collaborate with backend, frontend, and product teams to build scalable production systems. Participate in architectural and design decisions across AI, backend, and data workflows. 🛠️ Key Technologies & Tools Languages & Frameworks : Python, FastAPI, Flask, LangChain, PyTorch, TensorFlow, HuggingFace Transformers Voice & Audio : Whisper, Wav2Vec2.0, DeepSpeech, pyannote.audio, AssemblyAI, Kaldi, Mozilla TTS Vector DBs & RAG : FAISS, Pinecone, Weaviate, ChromaDB, LlamaIndex, LangGraph LLMs & GenAI APIs : OpenAI GPT-4/3.5, Gemini, Claude, Mistral, Meta LLaMA 2/3 DevOps & Deployment : Docker, GitHub Actions, CI/CD, Redis, Kafka, Kubernetes, AWS (EC2, Lambda, S3) Databases : MongoDB, Postgres, MySQL, Pinecone, TimescaleDB Monitoring & Logging : Prometheus, Grafana, Sentry, Elastic Stack (ELK) 🎯 Requirements & Qualifications 👨‍💻 Experience 2-6 years of experience in building and deploying AI/ML systems, with at least 2+ years in NLP or voice technologies. Proven track record of production deployment of ASR, STT, NLP, or GenAI models. Hands-on experience building systems involving vector databases, real-time pipelines, or LLM integrations. 📚 Educational Background Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Tier 1 institute preferred (IITs, BITS, IIITs, NITs, or global top 100 universities). ⚙️ Technical Skills Strong coding experience in Python and familiarity with FastAPI/Django. Understanding of distributed architectures, memory management, and latency optimization. Familiarity with transformer-based model architectures, training techniques, and data pipeline design. 💡 Bonus Experience Worked on multilingual speech recognition and translation. Experience deploying AI models on edge devices or browsers. Built or contributed to open-source ML/NLP projects. Published papers or patents in voice, NLP, or deep learning domains. 🚀 What Success Looks Like in 6 Months Lead the deployment of a real-time STT + diarization system for at least 1 enterprise client. Deliver high-accuracy nudge generation pipeline using RAG and summarization models. Build an in-house knowledge indexing + vector DB framework integrated into the product. Mentor 2–3 AI engineers and own execution across multiple modules. Achieve <1 sec latency on real-time voice-to-nudge pipeline from capture to recommendation. 💼 What We Offer Compensation : Competitive fixed salary + equity + performance-based bonuses Impact : Ownership of key AI modules powering thousands of live enterprise conversations Learning : Access to high-compute GPUs, API credits, research tools, and conference sponsorships Culture : High-trust, outcome-first environment that celebrates execution and learning Mentorship : Work directly with founders, ex-Microsoft, IIT-IIM-BITS alums, and top AI engineers Scale : Opportunity to scale an AI product from 10 clients to 100+ globally within 12 months ⚠️ This Role is NOT for Everyone 🚫 If you're looking for a slow, abstract research role—this is NOT for you. 🚫 If you're used to months of ideation before shipping—you won't enjoy our speed. 🚫 If you're not comfortable being hands-on and diving into scrappy builds—you may struggle. ✅ But if you’re a builder , architect , and visionary —who loves solving hard technical problems and delivering real-time AI at scale, we want to talk to you. 📩 How to Apply Send your CV, GitHub/portfolio, and a brief note on “Why AI at Darwix?” to: 📧 careers@cur8.in Subject Line: Application – AI Engineer – [Your Name] Include links to: Any relevant open-source contributions LLM/STT models you've fine-tuned or deployed RAG pipelines you've worked on 🔍 Final Thought This is not just a job. This is your opportunity to build the world’s most scalable AI sales intelligence platform —from India, for the world.

Job description 🚀 Job Title: ML Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 2-6 Years Level : Senior Level 🌐 About Darwix AI Darwix AI is one of India’s fastest-growing GenAI startups, revolutionizing the future of enterprise sales and customer engagement with real-time conversational intelligence. We are building a GenAI-powered agent-assist and pitch intelligence suite that captures, analyzes, and enhances every customer interaction—across voice, video, and chat—in real time. We serve leading enterprise clients across India, the UAE, and Southeast Asia and are backed by global VCs, top operators from Google, Salesforce, and McKinsey, and CXOs from the industry. This is your opportunity to join a high-caliber founding tech team solving frontier problems in real-time voice AI, multilingual transcription, retrieval-augmented generation (RAG), and fine-tuned LLMs at scale. 🧠 Role Overview As the ML Engineer , you will drive the development, deployment, and optimization of AI systems that power Darwix AI's real-time conversation intelligence platform. This includes voice-to-text transcription, speaker diarization, GenAI summarization, prompt engineering, knowledge retrieval, and real-time nudge delivery. You will lead a team of AI engineers and work closely with product managers, software architects, and data teams to ensure technical excellence, scalable architecture, and rapid iteration cycles. This is a high-ownership, hands-on leadership role where you will code, architect, and lead simultaneously. 🔧 Key Responsibilities 1. AI Architecture & Model Development Architect end-to-end AI pipelines for transcription, real-time inference, LLM integration, and vector-based retrieval. Build, fine-tune, and deploy STT models (Whisper, Wav2Vec2.0) and diarization systems for speaker separation. Implement GenAI pipelines using OpenAI, Gemini, LLaMA, Mistral, and other LLM APIs or open-source models. 2. Real-Time Voice AI System Development Design low-latency pipelines for capturing and processing audio in real-time across multi-lingual environments. Work on WebSocket-based bi-directional audio streaming, chunked inference, and result caching. Develop asynchronous, event-driven architectures for voice processing and decision-making. 3. RAG & Knowledge Graph Pipelines Create retrieval-augmented generation (RAG) systems that pull from structured and unstructured knowledge bases. Build vector DB architectures (e.g., FAISS, Pinecone, Weaviate) and connect to LangChain/LlamaIndex workflows. Own chunking, indexing, and embedding strategies (OpenAI, Cohere, Hugging Face embeddings). 4. Fine-Tuning & Prompt Engineering Fine-tune LLMs and foundational models using RLHF, SFT, PEFT (e.g., LoRA) as needed. Optimize prompts for summarization, categorization, tone analysis, objection handling, etc. Perform few-shot and zero-shot evaluations for quality benchmarking. 5. Pipeline Optimization & MLOps Ensure high availability and robustness of AI pipelines using CI/CD tools, Docker, Kubernetes, and GitHub Actions. Work with data engineering to streamline data ingestion, labeling, augmentation, and evaluation. Build internal tools to benchmark latency, accuracy, and relevance for production-grade AI features. 6. Team Leadership & Cross-Functional Collaboration Lead, mentor, and grow a high-performing AI engineering team. Collaborate with backend, frontend, and product teams to build scalable production systems. Participate in architectural and design decisions across AI, backend, and data workflows. 🛠️ Key Technologies & Tools Languages & Frameworks : Python, FastAPI, Flask, LangChain, PyTorch, TensorFlow, HuggingFace Transformers Voice & Audio : Whisper, Wav2Vec2.0, DeepSpeech, pyannote.audio, AssemblyAI, Kaldi, Mozilla TTS Vector DBs & RAG : FAISS, Pinecone, Weaviate, ChromaDB, LlamaIndex, LangGraph LLMs & GenAI APIs : OpenAI GPT-4/3.5, Gemini, Claude, Mistral, Meta LLaMA 2/3 DevOps & Deployment : Docker, GitHub Actions, CI/CD, Redis, Kafka, Kubernetes, AWS (EC2, Lambda, S3) Databases : MongoDB, Postgres, MySQL, Pinecone, TimescaleDB Monitoring & Logging : Prometheus, Grafana, Sentry, Elastic Stack (ELK) 🎯 Requirements & Qualifications 👨‍💻 Experience 2-6 years of experience in building and deploying AI/ML systems, with at least 2+ years in NLP or voice technologies. Proven track record of production deployment of ASR, STT, NLP, or GenAI models. Hands-on experience building systems involving vector databases, real-time pipelines, or LLM integrations. 📚 Educational Background Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Tier 1 institute preferred (IITs, BITS, IIITs, NITs, or global top 100 universities). ⚙️ Technical Skills Strong coding experience in Python and familiarity with FastAPI/Django. Understanding of distributed architectures, memory management, and latency optimization. Familiarity with transformer-based model architectures, training techniques, and data pipeline design. 💡 Bonus Experience Worked on multilingual speech recognition and translation. Experience deploying AI models on edge devices or browsers. Built or contributed to open-source ML/NLP projects. Published papers or patents in voice, NLP, or deep learning domains. 🚀 What Success Looks Like in 6 Months Lead the deployment of a real-time STT + diarization system for at least 1 enterprise client. Deliver high-accuracy nudge generation pipeline using RAG and summarization models. Build an in-house knowledge indexing + vector DB framework integrated into the product. Mentor 2–3 AI engineers and own execution across multiple modules. Achieve <1 sec latency on real-time voice-to-nudge pipeline from capture to recommendation. 💼 What We Offer Compensation : Competitive fixed salary + equity + performance-based bonuses Impact : Ownership of key AI modules powering thousands of live enterprise conversations Learning : Access to high-compute GPUs, API credits, research tools, and conference sponsorships Culture : High-trust, outcome-first environment that celebrates execution and learning Mentorship : Work directly with founders, ex-Microsoft, IIT-IIM-BITS alums, and top AI engineers Scale : Opportunity to scale an AI product from 10 clients to 100+ globally within 12 months ⚠️ This Role is NOT for Everyone 🚫 If you're looking for a slow, abstract research role—this is NOT for you. 🚫 If you're used to months of ideation before shipping—you won't enjoy our speed. 🚫 If you're not comfortable being hands-on and diving into scrappy builds—you may struggle. ✅ But if you’re a builder , architect , and visionary —who loves solving hard technical problems and delivering real-time AI at scale, we want to talk to you. 📩 How to Apply Send your CV, GitHub/portfolio, and a brief note on “Why AI at Darwix?” to: 📧 careers@cur8.in / vishnu.sethi@cur8.in Subject Line: Application – ML Engineer – [Your Name] Include links to: Any relevant open-source contributions LLM/STT models you've fine-tuned or deployed RAG pipelines you've worked on 🔍 Final Thought This is not just a job. This is your opportunity to build the world’s most scalable AI sales intelligence platform —from India, for the world.

🚀 Job Title: Lead AI Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 2-6 Years Level : Senior Level 🌐 About Darwix AI Darwix AI is one of India’s fastest-growing GenAI startups, revolutionizing the future of enterprise sales and customer engagement with real-time conversational intelligence. We are building a GenAI-powered agent-assist and pitch intelligence suite that captures, analyzes, and enhances every customer interaction—across voice, video, and chat—in real time. We serve leading enterprise clients across India, the UAE, and Southeast Asia and are backed by global VCs, top operators from Google, Salesforce, and McKinsey, and CXOs from the industry. This is your opportunity to join a high-caliber founding tech team solving frontier problems in real-time voice AI, multilingual transcription, retrieval-augmented generation (RAG), and fine-tuned LLMs at scale. 🧠 Role Overview As the Lead AI Engineer , you will drive the development, deployment, and optimization of AI systems that power Darwix AI's real-time conversation intelligence platform. This includes voice-to-text transcription, speaker diarization, GenAI summarization, prompt engineering, knowledge retrieval, and real-time nudge delivery. You will lead a team of AI engineers and work closely with product managers, software architects, and data teams to ensure technical excellence, scalable architecture, and rapid iteration cycles. This is a high-ownership, hands-on leadership role where you will code, architect, and lead simultaneously. 🔧 Key Responsibilities 1. AI Architecture & Model Development Architect end-to-end AI pipelines for transcription, real-time inference, LLM integration, and vector-based retrieval. Build, fine-tune, and deploy STT models (Whisper, Wav2Vec2.0) and diarization systems for speaker separation. Implement GenAI pipelines using OpenAI, Gemini, LLaMA, Mistral, and other LLM APIs or open-source models. 2. Real-Time Voice AI System Development Design low-latency pipelines for capturing and processing audio in real-time across multi-lingual environments. Work on WebSocket-based bi-directional audio streaming, chunked inference, and result caching. Develop asynchronous, event-driven architectures for voice processing and decision-making. 3. RAG & Knowledge Graph Pipelines Create retrieval-augmented generation (RAG) systems that pull from structured and unstructured knowledge bases. Build vector DB architectures (e.g., FAISS, Pinecone, Weaviate) and connect to LangChain/LlamaIndex workflows. Own chunking, indexing, and embedding strategies (OpenAI, Cohere, Hugging Face embeddings). 4. Fine-Tuning & Prompt Engineering Fine-tune LLMs and foundational models using RLHF, SFT, PEFT (e.g., LoRA) as needed. Optimize prompts for summarization, categorization, tone analysis, objection handling, etc. Perform few-shot and zero-shot evaluations for quality benchmarking. 5. Pipeline Optimization & MLOps Ensure high availability and robustness of AI pipelines using CI/CD tools, Docker, Kubernetes, and GitHub Actions. Work with data engineering to streamline data ingestion, labeling, augmentation, and evaluation. Build internal tools to benchmark latency, accuracy, and relevance for production-grade AI features. 6. Team Leadership & Cross-Functional Collaboration Lead, mentor, and grow a high-performing AI engineering team. Collaborate with backend, frontend, and product teams to build scalable production systems. Participate in architectural and design decisions across AI, backend, and data workflows. 🛠️ Key Technologies & Tools Languages & Frameworks : Python, FastAPI, Flask, LangChain, PyTorch, TensorFlow, HuggingFace Transformers Voice & Audio : Whisper, Wav2Vec2.0, DeepSpeech, pyannote.audio, AssemblyAI, Kaldi, Mozilla TTS Vector DBs & RAG : FAISS, Pinecone, Weaviate, ChromaDB, LlamaIndex, LangGraph LLMs & GenAI APIs : OpenAI GPT-4/3.5, Gemini, Claude, Mistral, Meta LLaMA 2/3 DevOps & Deployment : Docker, GitHub Actions, CI/CD, Redis, Kafka, Kubernetes, AWS (EC2, Lambda, S3) Databases : MongoDB, Postgres, MySQL, Pinecone, TimescaleDB Monitoring & Logging : Prometheus, Grafana, Sentry, Elastic Stack (ELK) 🎯 Requirements & Qualifications 👨‍💻 Experience 2-6 years of experience in building and deploying AI/ML systems, with at least 2+ years in NLP or voice technologies. Proven track record of production deployment of ASR, STT, NLP, or GenAI models. Hands-on experience building systems involving vector databases, real-time pipelines, or LLM integrations. 📚 Educational Background Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Tier 1 institute preferred (IITs, BITS, IIITs, NITs, or global top 100 universities). ⚙️ Technical Skills Strong coding experience in Python and familiarity with FastAPI/Django. Understanding of distributed architectures, memory management, and latency optimization. Familiarity with transformer-based model architectures, training techniques, and data pipeline design. 💡 Bonus Experience Worked on multilingual speech recognition and translation. Experience deploying AI models on edge devices or browsers. Built or contributed to open-source ML/NLP projects. Published papers or patents in voice, NLP, or deep learning domains. 🚀 What Success Looks Like in 6 Months Lead the deployment of a real-time STT + diarization system for at least 1 enterprise client. Deliver high-accuracy nudge generation pipeline using RAG and summarization models. Build an in-house knowledge indexing + vector DB framework integrated into the product. Mentor 2–3 AI engineers and own execution across multiple modules. Achieve <1 sec latency on real-time voice-to-nudge pipeline from capture to recommendation. 💼 What We Offer Compensation : Competitive fixed salary + equity + performance-based bonuses Impact : Ownership of key AI modules powering thousands of live enterprise conversations Learning : Access to high-compute GPUs, API credits, research tools, and conference sponsorships Culture : High-trust, outcome-first environment that celebrates execution and learning Mentorship : Work directly with founders, ex-Microsoft, IIT-IIM-BITS alums, and top AI engineers Scale : Opportunity to scale an AI product from 10 clients to 100+ globally within 12 months ⚠️ This Role is NOT for Everyone 🚫 If you're looking for a slow, abstract research role—this is NOT for you. 🚫 If you're used to months of ideation before shipping—you won't enjoy our speed. 🚫 If you're not comfortable being hands-on and diving into scrappy builds—you may struggle. ✅ But if you’re a builder , architect , and visionary —who loves solving hard technical problems and delivering real-time AI at scale, we want to talk to you. 📩 How to Apply Send your CV, GitHub/portfolio, and a brief note on “Why AI at Darwix?” to: 📧 careers@cur8.in Subject Line: Application – Lead AI Engineer – [Your Name] Include links to: Any relevant open-source contributions LLM/STT models you've fine-tuned or deployed RAG pipelines you've worked on 🔍 Final Thought This is not just a job. This is your opportunity to build the world’s most scalable AI sales intelligence platform —from India, for the world.

Redefine the future of customer experiences. One conversation at a time. We’re changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you’re ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you’re in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing Nextiva is seeking a hands on, experienced, and visionary Engineering Manager to lead our AI Agents team within the Data & Intelligence Platform group. You will be responsible for leading a team that develops intelligent, multimodal AI agents (voice and chatbots) as part of Nextiva’s next-generation customer experience platform. You will apply expertise in machine learning and software engineering to build AI-driven features that transform how businesses engage with customers. This position offers the opportunity to work at the forefront of generative AI and multimodal interactions, creating scalable AI solutions that blend automation with the human touch to deliver exceptional customer experiences. Success in this role will be measured by your ability to deliver AI features that measurably improve customer experiences (e.g., higher self-service resolution rates, faster response times, improved user satisfaction) while maintaining high software quality and ethical AI standards. You will help Nextiva achieve a balanced integration of AI and human interaction, directly contributing to our CX-first vision. Key Responsibilities Team Leadership & Development: Lead, mentor, and grow a team of AI Software Engineers. Foster a culture of innovation, collaboration, and continuous learning. Provide technical guidance and career development support. Technical Oversight: Oversee the design, development, and deployment of AI agents for Nextiva’s products that understand and respond to customers in multiple formats (e.g., spoken voice, written text). Ensure delivery of high-quality, scalable, and reliable features. Guide the integration of NLP, speech recognition, and large language models into production systems. AI Model Integration: Integrate large language models and other AI/ML components into the Agentic AI Platform to enable capabilities such as question answering, task automation, sentiment analysis, and recommendations. Ensure that AI models and solutions perform effectively in real-world environments and at scale. Multimodal Interaction Systems: Build and integrate components for multimodal interactions, including speech-to-text, text-to-speech, and dialog management systems. Performance Optimization: Optimize AI algorithms and agent frameworks for performance, scalability, and reliability. Use data-driven methods to tune model accuracy and response times. Quality, Ethics & Compliance: Implement robust testing (unit, integration, end-to-end) for AI features to ensure reliability and correctness. Incorporate ethical AI practices, ensuring AI agent behavior is unbiased and compliant with privacy and security regulations. Cross-Functional Collaboration: Partner and collaborate across the product organization to define the roadmap for AI agent capabilities. Translate business goals into technical strategies and execution plans. Innovation & Thought Leadership: Stay current with advancements in AI, machine learning, and multimodal interaction systems. Drive innovation by evaluating and adopting emerging technologies. Qualifications Education & Experience: Bachelor’s degree in computer science, Software Engineering, or a related field (required). A Master’s degree in AI, Machine Learning, or a related discipline is strongly preferred. Equivalent practical experience in AI/ML development will also be considered. Experience: 8+ years of software development experience, including 3+ years in a technical leadership or management role. Proven track record in AI/ML product development. Proven experience developing production-grade software (e.g., backend services, APIs, data pipelines) in a collaborative team environment. AI/ML Expertise: Strong understanding of AI and machine learning fundamentals with hands-on experience in natural language processing (NLP) and/or deep learning. Familiarity with the latest AI advancements (e.g., transformer-based models, conversational AI frameworks) and a history of applying AI models to solve real-world problems. Technical Skills: Proficiency in programming languages commonly used for AI development, such as Python (with ML libraries like TensorFlow or PyTorch) and/or a general-purpose language like Java or C# for scalable systems. Experience with machine learning frameworks and libraries for NLP, speech, or computer vision (e.g., Hugging Face Transformers, OpenAI APIs, spaCy, Kaldi, AWS/GCP/Azure AI services) is expected. Multimodal Interaction Knowledge: Experience with speech and language technologies – for example, integrating speech-to-text (ASR) and text-to-speech (TTS) engines, or building chatbots and voice bots for conversational interfaces. Cloud & Scalability: Familiarity with cloud platforms and deploying AI/ML models at scale (AWS, Google Cloud, or Azure). Experience with microservices architecture and containerization (Docker, Kubernetes) for AI services. Leadership Skills: Demonstrated ability to lead high-performing engineering teams. Strong project management, communication, and stakeholder engagement skills. Nextiva DNA (Core Competencies) Nextiva’s most successful team members share common traits and behaviors: Drives Results: Action-oriented with a passion for solving problems. They bring clarity and simplicity to ambiguous situations, challenge the status quo, and ask what can be done differently. They lead and drive change, celebrating success to build more success. Critical Thinker: Understands the "why" and identifies key drivers, learning from the past. They are fact-based and data-driven, forward-thinking, and see problems a few steps ahead. They provide options, recommendations, and actions, understanding risks and dependencies. Right Attitude: They are team-oriented, collaborative, competitive, and hate losing. They are resilient, able to bounce back from setbacks, zoom in and out, and get in the trenches to help solve important problems. They cultivate a culture of service, learning, support, and respect, caring for customers and teams. Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical 🩺 - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance 💼 - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ⚖️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security💰 - Provident Fund & Gratuity Wellness 🤸‍ - Employee Assistance Program and comprehensive wellness initiatives Growth 🌱 - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what’s going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog.

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, Bangalore or Pune, India . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, Bangalore or Pune, India . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, India . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, India . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, India . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

Redefine the future of customer experiences. One conversation at a time. We're changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you're ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you're in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing Nextiva, a leader in business communications, is seeking a skilled AI Software Engineer to join our AI Agents team within our Data & Intelligence Platform group. In this role, you will develop intelligent, multimodal AI agents (voice and chatbots) as part of Nextiva's next-generation customer experience platform. You will apply expertise in machine learning and software engineering to build AI-driven features that transform how businesses engage with customers. This position offers the opportunity to work at the forefront of generative AI and multimodal interactions, creating scalable AI solutions that blend automation with the human touch to deliver exceptional customer experiences. Key Responsibilities Design & Develop AI Agents: Design, implement, and refine AI agents for Nextiva's products that understand and respond to customers in multiple formats (e.g., spoken voice, written text). Develop conversational logic and multimodal interaction flows leveraging state-of-the-art natural language processing (NLP) and speech recognition techniques. A I Model Integration: Integrate large language models and other AI/ML components into the Agentic AI Platform to enable capabilities such as question answering, task automation, sentiment analysis, and recommendations. Ensure that AI models and solutions perform effectively in real-world environments and at scale. Full Lifecycle Engineering: Own the end-to-end development lifecycle of AI features. Multimodal Interaction Systems: Build and integrate components for multimodal interactions, including speech-to-text, text-to-speech, and dialog management systems. Performance Optimization: Optimize AI algorithms and agent frameworks for performance, scalability, and reliability. Use data-driven methods to tune model accuracy and response times. Quality, Ethics & Compliance: Implement robust testing (unit, integration, end-to-end) for AI features to ensure reliability and correctness. Incorporate ethical AI practices, ensuring AI agent behavior is unbiased and compliant with privacy and security regulations. Documentation & Mentorship: Document AI agent designs, algorithms, and usage guidelines for future reference. Provide technical guidance and mentorship to junior engineers or new team members as needed. Success in this role will be measured by your ability to deliver AI features that measurably improve customer experiences (e.g., higher self-service resolution rates, faster response times, improved user satisfaction) while maintaining high software quality and ethical AI standards. You will help Nextiva achieve a balanced integration of AI and human interaction, directly contributing to our CX-first vision. Qualifications Education: Bachelor's degree in computer science, Software Engineering, or a related field (required). A Master's degree in AI, Machine Learning, or a related discipline is strongly preferred. Equivalent practical experience in AI/ML development will also be considered. Software Engineering Experience: 5+ years of professional software development experience, including at least 2+ years building AI or machine-learning powered applications. Proven experience developing production-grade software (e.g., backend services, APIs, data pipelines) in a collaborative team environment. AI/ML Expertise: Strong understanding of AI and machine learning fundamentals with hands-on experience in natural language processing (NLP) and/or deep learning. Familiarity with the latest AI advancements (e.g., transformer-based models, conversational AI frameworks) and a history of applying AI models to solve real-world problems. Technical Skills: Proficiency in programming languages commonly used for AI development, such as Python (with ML libraries like TensorFlow or PyTorch) and/or a general-purpose language like Java or C# for scalable systems. Experience with machine learning frameworks and libraries for NLP, speech, or computer vision (e.g., Hugging Face Transformers, OpenAI APIs, spaCy, Kaldi, AWS/GCP/Azure AI services) is expected. Multimodal Interaction Knowledge: Experience with speech and language technologies – for example, integrating speech-to-text (ASR) and text-to-speech (TTS) engines, or building chatbots and voice bots for conversational interfaces. C loud & Scalability: Familiarity with cloud platforms and deploying AI/ML models at scale (AWS, Google Cloud, or Azure). Experience with microservices architecture and containerization (Docker, Kubernetes) for AI services. Collaboration & Communication: Excellent teamwork and communication skills. Nextiva DNA (Core Competencies) Nextiva's most successful team members share common traits and behaviors: Drives Results: Action-oriented with a passion for solving problems. They bring clarity and simplicity to ambiguous situations, challenge the status quo, and ask what can be done differently. They lead and drive change, celebrating success to build more success. Critical Thinker: Understands the "why" and identifies key drivers, learning from the past. They are fact-based and data-driven, forward-thinking , and see problems a few steps ahead. They provide options, recommendations, and actions, understanding risks and dependencies. Right Attitude : They are team-oriented, collaborative, competitive, and hate losing. They are resilient, able to bounce back from setbacks, zoom in and out, and get in the trenches to help solve important problems. They cultivate a culture of service, learning, support, and respect, caring for customers and teams. Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security - Provident Fund & Gratuity Wellness ‍ - Employee Assistance Program and comprehensive wellness initiatives Growth - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what's going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog. #LI-PJ1 #LI-HYBRID

Redefine the future of customer experiences. One conversation at a time. We’re changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you’re ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you’re in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing Nextiva, a leader in business communications, is seeking a skilled AI Software Engineer to join our AI Agents team within our Data & Intelligence Platform group. In this role, you will develop intelligent, multimodal AI agents (voice and chatbots) as part of Nextiva’s next-generation customer experience platform. You will apply expertise in machine learning and software engineering to build AI-driven features that transform how businesses engage with customers. This position offers the opportunity to work at the forefront of generative AI and multimodal interactions, creating scalable AI solutions that blend automation with the human touch to deliver exceptional customer experiences. Key Responsibilities Design & Develop AI Agents: Design, implement, and refine AI agents for Nextiva’s products that understand and respond to customers in multiple formats (e.g., spoken voice, written text). Develop conversational logic and multimodal interaction flows leveraging state-of-the-art natural language processing (NLP) and speech recognition techniques. AI Model Integration: Integrate large language models and other AI/ML components into the Agentic AI Platform to enable capabilities such as question answering, task automation, sentiment analysis, and recommendations. Ensure that AI models and solutions perform effectively in real-world environments and at scale. Full Lifecycle Engineering: Own the end-to-end development lifecycle of AI features. Multimodal Interaction Systems: Build and integrate components for multimodal interactions, including speech-to-text, text-to-speech, and dialog management systems. Performance Optimization: Optimize AI algorithms and agent frameworks for performance, scalability, and reliability. Use data-driven methods to tune model accuracy and response times. Quality, Ethics & Compliance: Implement robust testing (unit, integration, end-to-end) for AI features to ensure reliability and correctness. Incorporate ethical AI practices, ensuring AI agent behavior is unbiased and compliant with privacy and security regulations. Documentation & Mentorship: Document AI agent designs, algorithms, and usage guidelines for future reference. Provide technical guidance and mentorship to junior engineers or new team members as needed. Success in this role will be measured by your ability to deliver AI features that measurably improve customer experiences (e.g., higher self-service resolution rates, faster response times, improved user satisfaction) while maintaining high software quality and ethical AI standards. You will help Nextiva achieve a balanced integration of AI and human interaction, directly contributing to our CX-first vision. Qualifications Education: Bachelor’s degree in computer science, Software Engineering, or a related field (required). A Master’s degree in AI, Machine Learning, or a related discipline is strongly preferred. Equivalent practical experience in AI/ML development will also be considered. Software Engineering Experience: 5+ years of professional software development experience, including at least 2+ years building AI or machine-learning powered applications. Proven experience developing production-grade software (e.g., backend services, APIs, data pipelines) in a collaborative team environment. AI/ML Expertise: Strong understanding of AI and machine learning fundamentals with hands-on experience in natural language processing (NLP) and/or deep learning. Familiarity with the latest AI advancements (e.g., transformer-based models, conversational AI frameworks) and a history of applying AI models to solve real-world problems. Technical Skills: Proficiency in programming languages commonly used for AI development, such as Python (with ML libraries like TensorFlow or PyTorch) and/or a general-purpose language like Java or C# for scalable systems. Experience with machine learning frameworks and libraries for NLP, speech, or computer vision (e.g., Hugging Face Transformers, OpenAI APIs, spaCy, Kaldi, AWS/GCP/Azure AI services) is expected. Multimodal Interaction Knowledge: Experience with speech and language technologies – for example, integrating speech-to-text (ASR) and text-to-speech (TTS) engines, or building chatbots and voice bots for conversational interfaces. Cloud & Scalability: Familiarity with cloud platforms and deploying AI/ML models at scale (AWS, Google Cloud, or Azure). Experience with microservices architecture and containerization (Docker, Kubernetes) for AI services. Collaboration & Communication: Excellent teamwork and communication skills. Nextiva DNA (Core Competencies) Nextiva’s most successful team members share common traits and behaviors: Drives Results: Action-oriented with a passion for solving problems. They bring clarity and simplicity to ambiguous situations, challenge the status quo, and ask what can be done differently. They lead and drive change, celebrating success to build more success. Critical Thinker: Understands the "why" and identifies key drivers, learning from the past. They are fact-based and data-driven, forward-thinking, and see problems a few steps ahead. They provide options, recommendations, and actions, understanding risks and dependencies. Right Attitude: They are team-oriented, collaborative, competitive, and hate losing. They are resilient, able to bounce back from setbacks, zoom in and out, and get in the trenches to help solve important problems. They cultivate a culture of service, learning, support, and respect, caring for customers and teams. Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical 🩺 - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance 💼 - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ⚖️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security💰 - Provident Fund & Gratuity Wellness 🤸‍ - Employee Assistance Program and comprehensive wellness initiatives Growth 🌱 - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what’s going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog.

Redefine the future of customer experiences. One conversation at a time. We’re changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you’re ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you’re in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing Nextiva is seeking a hands on, experienced, and visionary Engineering Manager to lead our AI Agents team within the Data & Intelligence Platform group. You will be responsible for leading a team that develops intelligent, multimodal AI agents (voice and chatbots) as part of Nextiva’s next-generation customer experience platform. You will apply expertise in machine learning and software engineering to build AI-driven features that transform how businesses engage with customers. This position offers the opportunity to work at the forefront of generative AI and multimodal interactions, creating scalable AI solutions that blend automation with the human touch to deliver exceptional customer experiences. Success in this role will be measured by your ability to deliver AI features that measurably improve customer experiences (e.g., higher self-service resolution rates, faster response times, improved user satisfaction) while maintaining high software quality and ethical AI standards. You will help Nextiva achieve a balanced integration of AI and human interaction, directly contributing to our CX-first vision. Key Responsibilities Team Leadership & Development: Lead, mentor, and grow a team of AI Software Engineers. Foster a culture of innovation, collaboration, and continuous learning. Provide technical guidance and career development support. Technical Oversight: Oversee the design, development, and deployment of AI agents for Nextiva’s products that understand and respond to customers in multiple formats (e.g., spoken voice, written text). Ensure delivery of high-quality, scalable, and reliable features. Guide the integration of NLP, speech recognition, and large language models into production systems. AI Model Integration: Integrate large language models and other AI/ML components into the Agentic AI Platform to enable capabilities such as question answering, task automation, sentiment analysis, and recommendations. Ensure that AI models and solutions perform effectively in real-world environments and at scale. Multimodal Interaction Systems: Build and integrate components for multimodal interactions, including speech-to-text, text-to-speech, and dialog management systems. Performance Optimization: Optimize AI algorithms and agent frameworks for performance, scalability, and reliability. Use data-driven methods to tune model accuracy and response times. Quality, Ethics & Compliance: Implement robust testing (unit, integration, end-to-end) for AI features to ensure reliability and correctness. Incorporate ethical AI practices, ensuring AI agent behavior is unbiased and compliant with privacy and security regulations. Cross-Functional Collaboration: Partner and collaborate across the product organization to define the roadmap for AI agent capabilities. Translate business goals into technical strategies and execution plans. Innovation & Thought Leadership: Stay current with advancements in AI, machine learning, and multimodal interaction systems. Drive innovation by evaluating and adopting emerging technologies. Qualifications Education & Experience: Bachelor’s degree in computer science, Software Engineering, or a related field (required). A Master’s degree in AI, Machine Learning, or a related discipline is strongly preferred. Equivalent practical experience in AI/ML development will also be considered. Experience: 8+ years of software development experience, including 3+ years in a technical leadership or management role. Proven track record in AI/ML product development. Proven experience developing production-grade software (e.g., backend services, APIs, data pipelines) in a collaborative team environment. AI/ML Expertise: Strong understanding of AI and machine learning fundamentals with hands-on experience in natural language processing (NLP) and/or deep learning. Familiarity with the latest AI advancements (e.g., transformer-based models, conversational AI frameworks) and a history of applying AI models to solve real-world problems. Technical Skills: Proficiency in programming languages commonly used for AI development, such as Python (with ML libraries like TensorFlow or PyTorch) and/or a general-purpose language like Java or C# for scalable systems. Experience with machine learning frameworks and libraries for NLP, speech, or computer vision (e.g., Hugging Face Transformers, OpenAI APIs, spaCy, Kaldi, AWS/GCP/Azure AI services) is expected. Multimodal Interaction Knowledge: Experience with speech and language technologies – for example, integrating speech-to-text (ASR) and text-to-speech (TTS) engines, or building chatbots and voice bots for conversational interfaces. Cloud & Scalability: Familiarity with cloud platforms and deploying AI/ML models at scale (AWS, Google Cloud, or Azure). Experience with microservices architecture and containerization (Docker, Kubernetes) for AI services. Leadership Skills: Demonstrated ability to lead high-performing engineering teams. Strong project management, communication, and stakeholder engagement skills. Nextiva DNA (Core Competencies) Nextiva’s most successful team members share common traits and behaviors: Drives Results: Action-oriented with a passion for solving problems. They bring clarity and simplicity to ambiguous situations, challenge the status quo, and ask what can be done differently. They lead and drive change, celebrating success to build more success. Critical Thinker: Understands the "why" and identifies key drivers, learning from the past. They are fact-based and data-driven, forward-thinking, and see problems a few steps ahead. They provide options, recommendations, and actions, understanding risks and dependencies. Right Attitude: They are team-oriented, collaborative, competitive, and hate losing. They are resilient, able to bounce back from setbacks, zoom in and out, and get in the trenches to help solve important problems. They cultivate a culture of service, learning, support, and respect, caring for customers and teams. Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical 🩺 - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance 💼 - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ⚖️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security💰 - Provident Fund & Gratuity Wellness 🤸‍ - Employee Assistance Program and comprehensive wellness initiatives Growth 🌱 - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what’s going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog.

All Positions Speech Architect Noida | 5-8 years Apply Now Welcome to BUSINESSNEXT, where we believe in maximizing your true potential while doing something purposeful. Our commitment to innovation and forward-thinking is reflected in everything we do, and we're looking for like-minded individuals to join our team. If you're looking for a rewarding career in a company that values your creativity, we invite you to explore this opportunity. The Opportunity We are looking for smart & creative candidates who want to Learn and Grow, and to Innovate because they love the challenge of solving business problems. BusinessNext is looking for bright and motivated Data Engineers to play a key role in building the next generation Enterprise Big Data Platform. Within this realm of cutting-edge technology, you'll play a pivotal role in shaping the future of digital innovation on a global scale. Objectives Aligned To This Role As a Speech Architect, you will lead the development of cutting-edge speech recognition and processing systems, focusing on complex tasks such as speaker diarization, automatic speech recognition (ASR), Sentiment/Emotion recognition and transcription. You will guide a team of engineers and collaborate closely with other departments to deliver high-impact solutions. What would you do? Leadership: Lead and mentor a team of speech engineers, providing technical guidance and ensuring the successful delivery of projects. System Design: Architect and design end-to-end speech processing pipelines, from data acquisition to model deployment. Ensure systems are scalable, efficient, and maintainable. Advanced Modeling: Develop and implement advanced machine learning models for speech recognition, speaker diarization, and related tasks. Utilize state-of-the-art techniques such as deep learning, transfer learning, and ensemble methods. Research and Development: Conduct research to explore new methodologies and tools in the field of speech processing. Publish findings and present at industry conferences. Performance Optimization: Continuously monitor and optimize system performance, focusing on accuracy, latency, and resource utilization. Collaboration: Work closely with product management, data science, and software engineering teams to define project requirements and deliver innovative solutions. Customer Interaction: Engage with customers to understand their needs and provide tailored speech solutions. Assist in troubleshooting and optimizing deployed systems. Documentation and Standards: Establish and enforce best practices for code quality, documentation, and model management within the team. Required Skills Excellent knowledge in Python / Java programming. In-depth knowledge of speech processing frameworks like, Wave2vec, Kaldi, HTK, DeepSpeech and Whisper. Experience with NLP, STT, Speech to Speech LLMs and frameworks like Nvidia NEMO, PyAnnote. Proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, or Keras. Experience with large-scale ASR systems, speaker recognition, and diarization algorithms. Strong understanding of neural networks, sequence-to-sequence models, transformers and attention mechanisms. Familiarity with NLP techniques and their integration with speech systems. Expertise in deploying models on cloud platforms and optimizing for real-time applications. Good To Have Experience with low-latency streaming ASR systems. Knowledge of speech synthesis, STT (Speech-to-Text) and TTS (Text-to-Speech) systems. Experience in multilingual and low-resource speech processing. Educational Qualifications Bachelor’s, Master’s or Ph.D. in Computer Science, Electrical Engineering, or a related field. Good understanding of current technology trends along with ultra-scalable systems Proficient in effectively communicating with internal stakeholders across various domains, including technology and business. Meet The Team Connect with the team that loves the challenge of solving business problems, just like you! Ravi Kumar SVP Product Group Why BusinessNext? WIIFM, you ask? 😊 Well, lots of real, get-your-hands-dirty gigs, building cool products for the BFSI industry that is rapidly digitizing. Expect a challenging work experience that you’re unlikely to get in a Services Company. Come, #Unlimit your true Potential today to be #UpForTomorrow We exist for growth and development: We’re a company that is built on a Coaching Culture, committed to supporting employees to reach their full potential, helping them achieve their professional goals while contributing to the Moonshot. We thrive on clear, lucid Objectives & Key Results (OKRs). A trusting, transparent relationship where an Individual’s OKRs, lock into the department’s which, in turn, lock into the Company’s! We thrive by being proactive: Our Brand tagline "Up For Tomorrow" implies being proactive and forward-thinking, and our Culture Philosophy of "Unlimit" speaks of having no limits on what one can achieve. You can expect a culture that will constantly encourage you to take initiative and be proactive in your career, taking charge of your own professional development. Caring for People is our Business, and a Values-led Culture is our Profit. We just happen to use tech in the process. We’re a bunch of friends with Benefits: Coaching Sessions, Training and development opportunities, flexible working hours, and remote work options are just some of the perks of this Culture. Designed around you the employee so you can take advantage of opportunities to grow and develop and be ready for the future. Some quick facts Ours is an inspiring Garage-to-Unicorn Product story that has been scripted by gifted technologists who’re just like you. We are among the fastest growing SaaS companies in India, especially in the BFSI industry, with a global footprint, serving over 1 million+ users across 50+ countries Our clientele is based out in Asia Pac, USA, Middle East, South Africa, Australia, etc. Our product engages millions of global users, and we keep adding millions every month We are on a mission We sure are - on an 8-year Moon-shot Mission to be specific. We want to accelerate the World’s transition to intuitive, digital, and joyful financial experiences and become a Decacorn in the process. Does this excite you, then join us! 😊 Apply Now

Job Role: ML Research Engineer - ASR (Automatic Speech Recognition) Experience : 2+ years of experience Location: Chennai, Tamil Nadu About the Company: Kaizen being a reputed company is involved in the business of Kaizen Secure Voiz Private Limited is Six-year young company specializing in unified voice interactions management using latest technologies with Global presence for Supply, implementation, testing and commissioning of voice biometrics solution. KSV has good experience in design, development and implementation of such voice biometrics- based technologies and has enabled multi-channel applications such as mobile applications, voice bots, interactive voice response and call center-based services to target group. KSV has proposed options to customers, keeping the world trend on latest technologies. KSV has deployed similar solutions for various companies and understands domain very well. While KSV has proposed voice biometrics-based Interactions management platform is suitable for further scaling and improvements of customer experience using voice analytics solutions later. The introduction of such automation will not only save huge money for the company, but also exponentially increase the customer experience. Responsibilities: Develop and implement Voice Biometric algorithms and models. Evaluate and analyze the performance of Voice Biometric systems. Implement advanced security measures to protect biometric data and ensure compliance with privacy regulations. Optimize the performance of biometric systems to ensure fast and accurate identification and authentication. Fine-tune algorithms and parameters to improve system efficiency and reliability. Collaborate with cross-functional teams to integrate Voice Biometric solutions into various applications and systems. Stay updated with the latest advancements in Voice Biometric technology and contribute to research activities. Impeccable analytical and problem-solving skills Extensive math and computer skills, with a deep understanding of probability, statistics, and algorithms In-depth knowledge of machine learning frameworks, like Keras, PyTorch, etc Familiarity with data structures, data modelling, and software architecture Excellent time management and organizational skills Requirements: Bachelor's degree in computer science, data science, mathematics, or a related field. Master’s degree in computational linguistics, data analytics, or similar will be advantageous. At least two years' experience as a machine learning engineer. Advanced proficiency with Python, Java, and C code writing. In-depth knowledge of Deep Learning and Machine Learning Algorithms. Strong knowledge of Kaldi, Speechbrain, Wespeaker, 3D-Speaker, Unispeech, Nemo etc. Proficiency in speaker verification, Speaker Identification, Speaker Diarization, Anti-spoofing. Strong programming and algorithm development skills. Ability to work independently and as part of a team. Basic knowledge in signal processing. Job Type: Full-time Pay: ₹700,000.00 - ₹1,000,000.00 per year Schedule: Day shift Work Location: In person Application Deadline: 12/07/2025

Job Role: ML Research Engineer - ASR (Automatic Speech Recognition) Experience : 2+ years of experience Location: Chennai, Tamil Nadu About the Company: Kaizen being a reputed company is involved in the business of Kaizen Secure Voiz Private Limited is Six-year young company specializing in unified voice interactions management using latest technologies with Global presence for Supply, implementation, testing and commissioning of voice biometrics solution. KSV has good experience in design, development and implementation of such voice biometrics- based technologies and has enabled multi-channel applications such as mobile applications, voice bots, interactive voice response and call center-based services to target group. KSV has proposed options to customers, keeping the world trend on latest technologies. KSV has deployed similar solutions for various companies and understands domain very well. While KSV has proposed voice biometrics-based Interactions management platform is suitable for further scaling and improvements of customer experience using voice analytics solutions later. The introduction of such automation will not only save huge money for the company, but also exponentially increase the customer experience. Responsibilities: Develop and implement Voice Biometric algorithms and models. Evaluate and analyze the performance of Voice Biometric systems. Implement advanced security measures to protect biometric data and ensure compliance with privacy regulations. Optimize the performance of biometric systems to ensure fast and accurate identification and authentication. Fine-tune algorithms and parameters to improve system efficiency and reliability. Collaborate with cross-functional teams to integrate Voice Biometric solutions into various applications and systems. Stay updated with the latest advancements in Voice Biometric technology and contribute to research activities. Impeccable analytical and problem-solving skills Extensive math and computer skills, with a deep understanding of probability, statistics, and algorithms In-depth knowledge of machine learning frameworks, like Keras, PyTorch, etc Familiarity with data structures, data modelling, and software architecture Excellent time management and organizational skills Requirements: Bachelor's degree in computer science, data science, mathematics, or a related field. Master’s degree in computational linguistics, data analytics, or similar will be advantageous. At least two years' experience as a machine learning engineer. Advanced proficiency with Python, Java, and C code writing. In-depth knowledge of Deep Learning and Machine Learning Algorithms. Strong knowledge of Kaldi, Speechbrain, Wespeaker, 3D-Speaker, Unispeech, Nemo etc. Proficiency in speaker verification, Speaker Identification, Speaker Diarization, Anti-spoofing. Strong programming and algorithm development skills. Ability to work independently and as part of a team. Basic knowledge in signal processing. Job Type: Full-time Pay: ₹700,000.00 - ₹1,000,000.00 per year Schedule: Day shift Work Location: In person Application Deadline: 12/07/2025

About the Role: We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities 1. Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. 2. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. 3. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. 4. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Required Skills & Qualifications: Technical Skills 5+ Years of Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models. What do you get in return? Competitive Salary: Your skills and contributions are highly valued here, and we make sure your salary reflects that, rewarding you fairly for the knowledge and experience you bring to the table. Dynamic Career Growth: Our vibrant environment offers you the opportunity to grow rapidly, providing the right tools, mentorship, and experiences to fast-track your career. Idea Tanks : Innovation lives here. Our "Idea Tanks" are your playground to pitch, experiment, and collaborate on ideas that can shape the future. Growth Chats : Dive into our casual "Growth Chats" where you can learn from the best whether it's over lunch or during a laid-back session with peers, it's the perfect space to grow your skills. Snack Zone: Stay fueled and inspired! In our Snack Zone, you'll find a variety of snacks to keep your energy high and ideas flowing. Recognition & Rewards : We believe great work deserves to be recognized. Expect regular Hive-Fives, shoutouts and the chance to see your ideas come to life as part of our reward program. Fuel Your Growth Journey with Certifications: We’re all about your growth groove! Level up your skills with our support as we cover the cost of your certifications .

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, India . 📝 Interview Process: The process consists of 6 stages , including a technical assessment, code review, code discussion , and panel interviews . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

Job Title: Voice Processing Specialist Location: Remote /Jaipur Job Type: Full-time / Contract Experience: 3+ years expertise in voice cloning, transformation, and synthesis technologies Job Summary We are seeking a talented and motivated Voice Processing Specialist to join our team and lead the development of innovative voice technologies. The ideal candidate will have a deep understanding of speech synthesis, voice cloning, and transformation techniques. You will play a critical role in designing, implementing, and deploying state-of-the-art voice models that enhance naturalness, personalization, and flexibility of speech in AI-powered applications. This role is perfect for someone passionate about advancing human-computer voice interaction and creating lifelike, adaptive voice systems. Key Responsibilities Design, develop, and optimize advanced deep learning models for voice cloning, text-to-speech (TTS), voice conversion, and real-time voice transformation. Implement speaker embedding and voice identity preservation techniques to support accurate and high-fidelity voice replication. Work with large-scale and diverse audio datasets, including preprocessing, segmentation, normalization, and data augmentation to improve model generalization and robustness. Collaborate closely with data scientists, ML engineers, and product teams to integrate developed voice models into production pipelines. Fine-tune neural vocoders and synthesis architectures for better voice naturalness and emotional range. Stay current with the latest advancements in speech processing, AI voice synthesis, and deep generative models through academic literature and open-source projects. Contribute to the development of tools and APIs for deploying models on cloud and edge environments with high efficiency and low latency. Required Skills Strong understanding of speech signal processing, speech synthesis, and automatic speech recognition (ASR) systems. Hands-on experience with voice cloning frameworks such as Descript Overdub, Coqui TTS, SV2TTS, Tacotron, FastSpeech, or similar. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow. Experience working with speech libraries and toolkits such as ESPnet, Kaldi, Librosa, or SpeechBrain. In-depth knowledge of mel spectrograms, vocoder architectures (e.g., WaveNet, HiFi-GAN, WaveGlow), and their role in speech synthesis. Familiarity with REST APIs, model deployment, and cloud-based inference systems using platforms like AWS, Azure, or GCP. Ability to optimize models for performance in real-time or low-latency environments. Preferred Qualifications Experience in real-time voice transformation, including pitch shifting, timing modification, or emotion modulation. Exposure to emotion-aware speech synthesis, multilingual voice models, or prosody modeling. Design, develop, and optimize advanced deep learning models for voice cloning, text-to-speech (TTS), voice conversion, and real-time voice transformation Background in audio DSP (Digital Signal Processing) and speech analysis techniques. Previous contributions to open-source speech AI projects or publications in relevant domains. Why Join Us You will be part of a fast-moving, collaborative team working at the forefront of voice AI innovation. This role offers the opportunity to make a significant impact on products that reach millions of users, helping to shape the future of interactive voice experiences. Skills: automatic speech recognition (asr),vocoder architectures,voice cloning,voice processing,data,real-time voice transformation,speech synthesis,pytorch,tensorflow,voice conversion,speech signal processing,audio dsp,rest apis,python,cloud deployment,transformation,mel spectrograms,deep learning

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, India . 📝 Interview Process: The process consists of 6 stages , including a technical assessment, code review, code discussion , and panel interviews . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

🚀 Job Title: AI Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 2-6 Years Level : Senior Level 🌐 About Darwix AI Darwix AI is one of India’s fastest-growing GenAI startups, revolutionizing the future of enterprise sales and customer engagement with real-time conversational intelligence. We are building a GenAI-powered agent-assist and pitch intelligence suite that captures, analyzes, and enhances every customer interaction—across voice, video, and chat—in real time. We serve leading enterprise clients across India, the UAE, and Southeast Asia and are backed by global VCs, top operators from Google, Salesforce, and McKinsey, and CXOs from the industry. This is your opportunity to join a high-caliber founding tech team solving frontier problems in real-time voice AI, multilingual transcription, retrieval-augmented generation (RAG), and fine-tuned LLMs at scale. 🧠 Role Overview As the AI Engineer , you will drive the development, deployment, and optimization of AI systems that power Darwix AI's real-time conversation intelligence platform. This includes voice-to-text transcription, speaker diarization, GenAI summarization, prompt engineering, knowledge retrieval, and real-time nudge delivery. You will lead a team of AI engineers and work closely with product managers, software architects, and data teams to ensure technical excellence, scalable architecture, and rapid iteration cycles. This is a high-ownership, hands-on leadership role where you will code, architect, and lead simultaneously. 🔧 Key Responsibilities 1. AI Architecture & Model Development Architect end-to-end AI pipelines for transcription, real-time inference, LLM integration, and vector-based retrieval. Build, fine-tune, and deploy STT models (Whisper, Wav2Vec2.0) and diarization systems for speaker separation. Implement GenAI pipelines using OpenAI, Gemini, LLaMA, Mistral, and other LLM APIs or open-source models. 2. Real-Time Voice AI System Development Design low-latency pipelines for capturing and processing audio in real-time across multi-lingual environments. Work on WebSocket-based bi-directional audio streaming, chunked inference, and result caching. Develop asynchronous, event-driven architectures for voice processing and decision-making. 3. RAG & Knowledge Graph Pipelines Create retrieval-augmented generation (RAG) systems that pull from structured and unstructured knowledge bases. Build vector DB architectures (e.g., FAISS, Pinecone, Weaviate) and connect to LangChain/LlamaIndex workflows. Own chunking, indexing, and embedding strategies (OpenAI, Cohere, Hugging Face embeddings). 4. Fine-Tuning & Prompt Engineering Fine-tune LLMs and foundational models using RLHF, SFT, PEFT (e.g., LoRA) as needed. Optimize prompts for summarization, categorization, tone analysis, objection handling, etc. Perform few-shot and zero-shot evaluations for quality benchmarking. 5. Pipeline Optimization & MLOps Ensure high availability and robustness of AI pipelines using CI/CD tools, Docker, Kubernetes, and GitHub Actions. Work with data engineering to streamline data ingestion, labeling, augmentation, and evaluation. Build internal tools to benchmark latency, accuracy, and relevance for production-grade AI features. 6. Team Leadership & Cross-Functional Collaboration Lead, mentor, and grow a high-performing AI engineering team. Collaborate with backend, frontend, and product teams to build scalable production systems. Participate in architectural and design decisions across AI, backend, and data workflows. 🛠️ Key Technologies & Tools Languages & Frameworks : Python, FastAPI, Flask, LangChain, PyTorch, TensorFlow, HuggingFace Transformers Voice & Audio : Whisper, Wav2Vec2.0, DeepSpeech, pyannote.audio, AssemblyAI, Kaldi, Mozilla TTS Vector DBs & RAG : FAISS, Pinecone, Weaviate, ChromaDB, LlamaIndex, LangGraph LLMs & GenAI APIs : OpenAI GPT-4/3.5, Gemini, Claude, Mistral, Meta LLaMA 2/3 DevOps & Deployment : Docker, GitHub Actions, CI/CD, Redis, Kafka, Kubernetes, AWS (EC2, Lambda, S3) Databases : MongoDB, Postgres, MySQL, Pinecone, TimescaleDB Monitoring & Logging : Prometheus, Grafana, Sentry, Elastic Stack (ELK) 🎯 Requirements & Qualifications 👨‍💻 Experience 2-6 years of experience in building and deploying AI/ML systems, with at least 2+ years in NLP or voice technologies. Proven track record of production deployment of ASR, STT, NLP, or GenAI models. Hands-on experience building systems involving vector databases, real-time pipelines, or LLM integrations. 📚 Educational Background Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Tier 1 institute preferred (IITs, BITS, IIITs, NITs, or global top 100 universities). ⚙️ Technical Skills Strong coding experience in Python and familiarity with FastAPI/Django. Understanding of distributed architectures, memory management, and latency optimization. Familiarity with transformer-based model architectures, training techniques, and data pipeline design. 💡 Bonus Experience Worked on multilingual speech recognition and translation. Experience deploying AI models on edge devices or browsers. Built or contributed to open-source ML/NLP projects. Published papers or patents in voice, NLP, or deep learning domains. 🚀 What Success Looks Like in 6 Months Lead the deployment of a real-time STT + diarization system for at least 1 enterprise client. Deliver high-accuracy nudge generation pipeline using RAG and summarization models. Build an in-house knowledge indexing + vector DB framework integrated into the product. Mentor 2–3 AI engineers and own execution across multiple modules. Achieve <1 sec latency on real-time voice-to-nudge pipeline from capture to recommendation. 💼 What We Offer Compensation : Competitive fixed salary + equity + performance-based bonuses Impact : Ownership of key AI modules powering thousands of live enterprise conversations Learning : Access to high-compute GPUs, API credits, research tools, and conference sponsorships Culture : High-trust, outcome-first environment that celebrates execution and learning Mentorship : Work directly with founders, ex-Microsoft, IIT-IIM-BITS alums, and top AI engineers Scale : Opportunity to scale an AI product from 10 clients to 100+ globally within 12 months ⚠️ This Role is NOT for Everyone 🚫 If you're looking for a slow, abstract research role—this is NOT for you. 🚫 If you're used to months of ideation before shipping—you won't enjoy our speed. 🚫 If you're not comfortable being hands-on and diving into scrappy builds—you may struggle. ✅ But if you’re a builder , architect , and visionary —who loves solving hard technical problems and delivering real-time AI at scale, we want to talk to you. 📩 How to Apply Send your CV, GitHub/portfolio, and a brief note on “Why AI at Darwix?” to: 📧 careers@cur8.in Subject Line: Application – AI Engineer – [Your Name] Include links to: Any relevant open-source contributions LLM/STT models you've fine-tuned or deployed RAG pipelines you've worked on 🔍 Final Thought This is not just a job. This is your opportunity to build the world’s most scalable AI sales intelligence platform —from India, for the world. Show more Show less

Company Description Bytezera is a data services provider that specialise in AI and data solutions to help businesses maximise their data potential. With expertise in data-driven solution design, machine learning, AI, data engineering, and analytics, we empower organizations to make informed decisions and drive innovation. Our focus is on using data to achieve competitive advantage and transformation. About the Role We are seeking a highly skilled and hands-on AI Engineer to drive the development of cutting-edge AI applications using the latest in Computer vision, STT, Large Language Models (LLMs) , agentic frameworks , and Generative AI technologies . This role covers the full AI development lifecycle—from data preparation and model training to deployment and optimization—with a strong focus on NLP and open-source foundation models . You will be directly involved in building and deploying goal-driven, autonomous AI agents and scalable AI systems for real-world use cases. Key Responsibilities Computer Vision Development Design and implement advanced computer vision models for object detection, image segmentation, tracking, facial recognition, OCR, and video analysis. Fine-tune and deploy vision models using frameworks like PyTorch, TensorFlow, OpenCV, Detectron2, YOLO, MMDetection , etc. Optimize inference pipelines for real-time vision processing across edge devices, GPUs, or cloud-based systems. Speech-to-Text (STT) System Development Build and fine-tune ASR (Automatic Speech Recognition) models using toolkits such as Whisper, NVIDIA NeMo, DeepSpeech, Kaldi, or wav2vec 2.0 . Develop multilingual and domain-specific STT pipelines optimized for real-time transcription and high accuracy. Integrate STT into downstream NLP pipelines or agentic systems for transcription, summarization, or intent recognition. LLM and Agentic AI Design & Development Build and deploy advanced LLM-based AI agents using frameworks such as LangGraph , CrewAI , AutoGen , and OpenAgents . Fine-tune and optimize open-source LLMs (e.g., GPT-4 , LLaMA 3 , Mistral , T5 ) for domain-specific applications. Design and implement retrieval-augmented generation (RAG) pipelines with vector databases like FAISS , Weaviate , or Pinecone . Develop NLP pipelines using Hugging Face Transformers , spaCy , and LangChain for various text understanding and generation tasks. Leverage Python with PyTorch and TensorFlow for training, fine-tuning, and evaluating models. Prepare and manage high-quality datasets for model training and evaluation. Experience & Qualifications 2+ years of hands-on experience in AI engineering , machine learning , or data science roles. Proven track record in building and deploying computer vision and STT AI application . Experience with agentic workflows or autonomous AI agents is highly desirable. Technical Skills Languages & Libraries:Python, PyTorch, TensorFlow, Hugging Face Transformers, LangChain, spaCy LLMs & Generative AI:GPT, LLaMA 3, Mistral, T5, Claude, and other open-source or commercial models Agentic Tooling:LangGraph, CrewAI, AutoGen, OpenAgents Vector databases (Pinecone or ChromaDB) DevOps & Deployment: Docker, Kubernetes, AWS (SageMaker, Lambda, Bedrock, S3) Core ML Skills: Data preprocessing, feature engineering, model evaluation, and optimization Qualifications:Education: Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field. Show more Show less

Job description 🚀 Job Title: AI Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 2-6 Years Level : Senior Level 🌐 About Darwix AI Darwix AI is one of India’s fastest-growing GenAI startups, revolutionizing the future of enterprise sales and customer engagement with real-time conversational intelligence. We are building a GenAI-powered agent-assist and pitch intelligence suite that captures, analyzes, and enhances every customer interaction—across voice, video, and chat—in real time. We serve leading enterprise clients across India, the UAE, and Southeast Asia and are backed by global VCs, top operators from Google, Salesforce, and McKinsey, and CXOs from the industry. This is your opportunity to join a high-caliber founding tech team solving frontier problems in real-time voice AI, multilingual transcription, retrieval-augmented generation (RAG), and fine-tuned LLMs at scale. 🧠 Role Overview As the AI Engineer , you will drive the development, deployment, and optimization of AI systems that power Darwix AI's real-time conversation intelligence platform. This includes voice-to-text transcription, speaker diarization, GenAI summarization, prompt engineering, knowledge retrieval, and real-time nudge delivery. You will lead a team of AI engineers and work closely with product managers, software architects, and data teams to ensure technical excellence, scalable architecture, and rapid iteration cycles. This is a high-ownership, hands-on leadership role where you will code, architect, and lead simultaneously. 🔧 Key Responsibilities 1. AI Architecture & Model Development Architect end-to-end AI pipelines for transcription, real-time inference, LLM integration, and vector-based retrieval. Build, fine-tune, and deploy STT models (Whisper, Wav2Vec2.0) and diarization systems for speaker separation. Implement GenAI pipelines using OpenAI, Gemini, LLaMA, Mistral, and other LLM APIs or open-source models. 2. Real-Time Voice AI System Development Design low-latency pipelines for capturing and processing audio in real-time across multi-lingual environments. Work on WebSocket-based bi-directional audio streaming, chunked inference, and result caching. Develop asynchronous, event-driven architectures for voice processing and decision-making. 3. RAG & Knowledge Graph Pipelines Create retrieval-augmented generation (RAG) systems that pull from structured and unstructured knowledge bases. Build vector DB architectures (e.g., FAISS, Pinecone, Weaviate) and connect to LangChain/LlamaIndex workflows. Own chunking, indexing, and embedding strategies (OpenAI, Cohere, Hugging Face embeddings). 4. Fine-Tuning & Prompt Engineering Fine-tune LLMs and foundational models using RLHF, SFT, PEFT (e.g., LoRA) as needed. Optimize prompts for summarization, categorization, tone analysis, objection handling, etc. Perform few-shot and zero-shot evaluations for quality benchmarking. 5. Pipeline Optimization & MLOps Ensure high availability and robustness of AI pipelines using CI/CD tools, Docker, Kubernetes, and GitHub Actions. Work with data engineering to streamline data ingestion, labeling, augmentation, and evaluation. Build internal tools to benchmark latency, accuracy, and relevance for production-grade AI features. 6. Team Leadership & Cross-Functional Collaboration Lead, mentor, and grow a high-performing AI engineering team. Collaborate with backend, frontend, and product teams to build scalable production systems. Participate in architectural and design decisions across AI, backend, and data workflows. 🛠️ Key Technologies & Tools Languages & Frameworks : Python, FastAPI, Flask, LangChain, PyTorch, TensorFlow, HuggingFace Transformers Voice & Audio : Whisper, Wav2Vec2.0, DeepSpeech, pyannote.audio, AssemblyAI, Kaldi, Mozilla TTS Vector DBs & RAG : FAISS, Pinecone, Weaviate, ChromaDB, LlamaIndex, LangGraph LLMs & GenAI APIs : OpenAI GPT-4/3.5, Gemini, Claude, Mistral, Meta LLaMA 2/3 DevOps & Deployment : Docker, GitHub Actions, CI/CD, Redis, Kafka, Kubernetes, AWS (EC2, Lambda, S3) Databases : MongoDB, Postgres, MySQL, Pinecone, TimescaleDB Monitoring & Logging : Prometheus, Grafana, Sentry, Elastic Stack (ELK) 🎯 Requirements & Qualifications 👨‍💻 Experience 2-6 years of experience in building and deploying AI/ML systems, with at least 2+ years in NLP or voice technologies. Proven track record of production deployment of ASR, STT, NLP, or GenAI models. Hands-on experience building systems involving vector databases, real-time pipelines, or LLM integrations. 📚 Educational Background Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Tier 1 institute preferred (IITs, BITS, IIITs, NITs, or global top 100 universities). ⚙️ Technical Skills Strong coding experience in Python and familiarity with FastAPI/Django. Understanding of distributed architectures, memory management, and latency optimization. Familiarity with transformer-based model architectures, training techniques, and data pipeline design. 💡 Bonus Experience Worked on multilingual speech recognition and translation. Experience deploying AI models on edge devices or browsers. Built or contributed to open-source ML/NLP projects. Published papers or patents in voice, NLP, or deep learning domains. 🚀 What Success Looks Like in 6 Months Lead the deployment of a real-time STT + diarization system for at least 1 enterprise client. Deliver high-accuracy nudge generation pipeline using RAG and summarization models. Build an in-house knowledge indexing + vector DB framework integrated into the product. Mentor 2–3 AI engineers and own execution across multiple modules. Achieve <1 sec latency on real-time voice-to-nudge pipeline from capture to recommendation. 💼 What We Offer Compensation : Competitive fixed salary + equity + performance-based bonuses Impact : Ownership of key AI modules powering thousands of live enterprise conversations Learning : Access to high-compute GPUs, API credits, research tools, and conference sponsorships Culture : High-trust, outcome-first environment that celebrates execution and learning Mentorship : Work directly with founders, ex-Microsoft, IIT-IIM-BITS alums, and top AI engineers Scale : Opportunity to scale an AI product from 10 clients to 100+ globally within 12 months ⚠️ This Role is NOT for Everyone 🚫 If you're looking for a slow, abstract research role—this is NOT for you. 🚫 If you're used to months of ideation before shipping—you won't enjoy our speed. 🚫 If you're not comfortable being hands-on and diving into scrappy builds—you may struggle. ✅ But if you’re a builder , architect , and visionary —who loves solving hard technical problems and delivering real-time AI at scale, we want to talk to you. 📩 How to Apply Send your CV, GitHub/portfolio, and a brief note on “Why AI at Darwix?” to: 📧 careers@cur8.in Subject Line: Application – AI Engineer – [Your Name] Include links to: Any relevant open-source contributions LLM/STT models you've fine-tuned or deployed RAG pipelines you've worked on 🔍 Final Thought This is not just a job. This is your opportunity to build the world’s most scalable AI sales intelligence platform —from India, for the world. Show more Show less

Job description 🚀 Job Title: ML Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 2-6 Years Level : Senior Level 🌐 About Darwix AI Darwix AI is one of India’s fastest-growing GenAI startups, revolutionizing the future of enterprise sales and customer engagement with real-time conversational intelligence. We are building a GenAI-powered agent-assist and pitch intelligence suite that captures, analyzes, and enhances every customer interaction—across voice, video, and chat—in real time. We serve leading enterprise clients across India, the UAE, and Southeast Asia and are backed by global VCs, top operators from Google, Salesforce, and McKinsey, and CXOs from the industry. This is your opportunity to join a high-caliber founding tech team solving frontier problems in real-time voice AI, multilingual transcription, retrieval-augmented generation (RAG), and fine-tuned LLMs at scale. 🧠 Role Overview As the ML Engineer , you will drive the development, deployment, and optimization of AI systems that power Darwix AI's real-time conversation intelligence platform. This includes voice-to-text transcription, speaker diarization, GenAI summarization, prompt engineering, knowledge retrieval, and real-time nudge delivery. You will lead a team of AI engineers and work closely with product managers, software architects, and data teams to ensure technical excellence, scalable architecture, and rapid iteration cycles. This is a high-ownership, hands-on leadership role where you will code, architect, and lead simultaneously. 🔧 Key Responsibilities 1. AI Architecture & Model Development Architect end-to-end AI pipelines for transcription, real-time inference, LLM integration, and vector-based retrieval. Build, fine-tune, and deploy STT models (Whisper, Wav2Vec2.0) and diarization systems for speaker separation. Implement GenAI pipelines using OpenAI, Gemini, LLaMA, Mistral, and other LLM APIs or open-source models. 2. Real-Time Voice AI System Development Design low-latency pipelines for capturing and processing audio in real-time across multi-lingual environments. Work on WebSocket-based bi-directional audio streaming, chunked inference, and result caching. Develop asynchronous, event-driven architectures for voice processing and decision-making. 3. RAG & Knowledge Graph Pipelines Create retrieval-augmented generation (RAG) systems that pull from structured and unstructured knowledge bases. Build vector DB architectures (e.g., FAISS, Pinecone, Weaviate) and connect to LangChain/LlamaIndex workflows. Own chunking, indexing, and embedding strategies (OpenAI, Cohere, Hugging Face embeddings). 4. Fine-Tuning & Prompt Engineering Fine-tune LLMs and foundational models using RLHF, SFT, PEFT (e.g., LoRA) as needed. Optimize prompts for summarization, categorization, tone analysis, objection handling, etc. Perform few-shot and zero-shot evaluations for quality benchmarking. 5. Pipeline Optimization & MLOps Ensure high availability and robustness of AI pipelines using CI/CD tools, Docker, Kubernetes, and GitHub Actions. Work with data engineering to streamline data ingestion, labeling, augmentation, and evaluation. Build internal tools to benchmark latency, accuracy, and relevance for production-grade AI features. 6. Team Leadership & Cross-Functional Collaboration Lead, mentor, and grow a high-performing AI engineering team. Collaborate with backend, frontend, and product teams to build scalable production systems. Participate in architectural and design decisions across AI, backend, and data workflows. 🛠️ Key Technologies & Tools Languages & Frameworks : Python, FastAPI, Flask, LangChain, PyTorch, TensorFlow, HuggingFace Transformers Voice & Audio : Whisper, Wav2Vec2.0, DeepSpeech, pyannote.audio, AssemblyAI, Kaldi, Mozilla TTS Vector DBs & RAG : FAISS, Pinecone, Weaviate, ChromaDB, LlamaIndex, LangGraph LLMs & GenAI APIs : OpenAI GPT-4/3.5, Gemini, Claude, Mistral, Meta LLaMA 2/3 DevOps & Deployment : Docker, GitHub Actions, CI/CD, Redis, Kafka, Kubernetes, AWS (EC2, Lambda, S3) Databases : MongoDB, Postgres, MySQL, Pinecone, TimescaleDB Monitoring & Logging : Prometheus, Grafana, Sentry, Elastic Stack (ELK) 🎯 Requirements & Qualifications 👨‍💻 Experience 2-6 years of experience in building and deploying AI/ML systems, with at least 2+ years in NLP or voice technologies. Proven track record of production deployment of ASR, STT, NLP, or GenAI models. Hands-on experience building systems involving vector databases, real-time pipelines, or LLM integrations. 📚 Educational Background Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Tier 1 institute preferred (IITs, BITS, IIITs, NITs, or global top 100 universities). ⚙️ Technical Skills Strong coding experience in Python and familiarity with FastAPI/Django. Understanding of distributed architectures, memory management, and latency optimization. Familiarity with transformer-based model architectures, training techniques, and data pipeline design. 💡 Bonus Experience Worked on multilingual speech recognition and translation. Experience deploying AI models on edge devices or browsers. Built or contributed to open-source ML/NLP projects. Published papers or patents in voice, NLP, or deep learning domains. 🚀 What Success Looks Like in 6 Months Lead the deployment of a real-time STT + diarization system for at least 1 enterprise client. Deliver high-accuracy nudge generation pipeline using RAG and summarization models. Build an in-house knowledge indexing + vector DB framework integrated into the product. Mentor 2–3 AI engineers and own execution across multiple modules. Achieve <1 sec latency on real-time voice-to-nudge pipeline from capture to recommendation. 💼 What We Offer Compensation : Competitive fixed salary + equity + performance-based bonuses Impact : Ownership of key AI modules powering thousands of live enterprise conversations Learning : Access to high-compute GPUs, API credits, research tools, and conference sponsorships Culture : High-trust, outcome-first environment that celebrates execution and learning Mentorship : Work directly with founders, ex-Microsoft, IIT-IIM-BITS alums, and top AI engineers Scale : Opportunity to scale an AI product from 10 clients to 100+ globally within 12 months ⚠️ This Role is NOT for Everyone 🚫 If you're looking for a slow, abstract research role—this is NOT for you. 🚫 If you're used to months of ideation before shipping—you won't enjoy our speed. 🚫 If you're not comfortable being hands-on and diving into scrappy builds—you may struggle. ✅ But if you’re a builder , architect , and visionary —who loves solving hard technical problems and delivering real-time AI at scale, we want to talk to you. 📩 How to Apply Send your CV, GitHub/portfolio, and a brief note on “Why AI at Darwix?” to: 📧 careers@cur8.in / vishnu.sethi@cur8.in Subject Line: Application – ML Engineer – [Your Name] Include links to: Any relevant open-source contributions LLM/STT models you've fine-tuned or deployed RAG pipelines you've worked on 🔍 Final Thought This is not just a job. This is your opportunity to build the world’s most scalable AI sales intelligence platform —from India, for the world. Show more Show less