9814 Tensorflow Jobs - Page 43

About ShellKode We are an innovation-first technology company focused on delivering cutting-edge solutions in Cloud, Data, and GenAI . As an AWS-exclusive partner, we serve startups and enterprises in accelerating their digital transformation journeys. At ShellKode, we build, ship, and scale solutions with purpose-driven AI. Who We Are Looking For We are hiring fresh graduates (Class of 2025) who are passionate about AI, Machine Learning, and Data Science . If you have a strong foundational understanding and are eager to work on real-world AI projects, join our fast-growing engineering team in Coimbatore . Preferred Qualifications Bachelor's Degree in Artificial Intelligence, Machine Learning, Data Science, or Computer Science with AI/ML specialization (Class of 2025). Strong academic projects or internships in AI, NLP, CV, or MLOps are a plus. Good knowledge of Python and foundational ML libraries like scikit-learn, pandas, numpy. Exposure to frameworks such as TensorFlow, PyTorch, or HuggingFace is a bonus. Understanding of cloud services (preferably AWS) is an added advantage. Solid understanding of algorithms, data structures, and model evaluation techniques. Skills: numpy,python,artificial intelligence,scikit-learn,aws,cloud services,data science,ai,pandas,ml,huggingface,data structures,algorithms,tensorflow,model evaluation,pytorch,machine learning

1. Organize training programs on Planning & Installation for all new dealers. 2. Maintain the profitability as per the costing furnished by sales team. 3. Handle all major projects and complete within the agreed timeline. 4. Visit all dealer jobs periodically and maintain the quality of Installation as per the standards. 5. Train and develop the dealer team on all new products introduced 6. Maintain good PR with all key customers during the installation stage and collect satisfaction letters. 7. Provide the necessary cost variance reports for all major jobs executed. 8. Release timely work orders to dealers on NAD / Key customer jobs. 9. Submit necessary documentations and bills to customers and facilitate timely collection. 10. Furnish continuous feedback on the product quality to the Product Managers and contribute for improvement. 11. Support Channel Partners with necessary spares during the pre commissioning failures 12. Prepare pre commissioning failure reports to Quality / Factory and get necessary credit to branch. 13. Claim timely insurance on damaged machines delivered at warehouse/sites and follow up for necessary settlement. 14. Ensure to get credits for spares issues during pre-commissioning failure from factory 15. Ensure there are no escalations, in case of any escalations resolve the same at earlie Key Responsibilities: Short Info Posted: 0 day(s) ago Location: Jaipur Qualifications: BE Experience: 3 Years - 0 Months To 6 Years - 0 Months

To lead a small team and ensure the seamless execution of delegate registration and data management for the Zak World of Fa ades conference series. This role is pivotal in delivering a high-quality registration experience for attendees, maintaining accurate data records, and supporting the overall success of the event operations. Qualification: Graduate. Preferably a PGDM in Events Management. Should have handled RSVP for 2-3 years. Fluency in spoken English is a must. . Please make sure to mention the title of the job position youre applying for in the subject line of your email.

HCLTech is looking for a highly talented and self- motivated [ Principal Software Engineer to join it in advancing the technological world through innovation and creativity. Job Title: Principal Software Engineer Role/Responsibilities Gen AI capability development - Design, fine-tune, and optimize LLMs, retrieval-augmented generation (RAG), and reinforcement learning models for IT automation. Experiment with cutting-edge AI techniques, including multi-agent architectures, prompt tuning, and continual learning. 6+ years of experience in a similar role, with a strong focus on developing & deploying machine learning models in production environments. Improve model accuracy, latency, and efficiency, ensuring optimal performance for deployed ML applications. Design and implement CI/CD pipelines for deploying machine learning models to production environments Automate the processes involved in training, testing, deploying, and monitoring models to ensure smooth and continuous operations. Develop tools and frameworks for monitoring model performance and stability in production, ensuring models remain accurate and effective over time. Work closely with data scientists and data engineers to integrate machine learning models with existing data infrastructure Manage cloud-based machine learning environments, ensuring scalability, security, and cost-efficiency. Optimize models for production, focusing on performance, scalability, and resource utilization Create and maintain comprehensive documentation for processes, pipelines, and system architecture. Proficiency in Python and demonstrable expertise in at-least one of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with LLMs and finetuning models Experience with CI/CD tools (e.g., Jenkins, GitLab CI, Gitub Actions) and containerization (e.g., Docker, Kubernetes). Hands-on Knowledge of cloud platforms (e.g., AWS, GCP, Azure, Databricks) and cloud-native tools for MLOps. Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack). Experience with infrastructure-as-code tools (e.g., Terraform, Ansible). Familiarity with data engineering workflows and ETL processes. Knowledge of model explainability and fairness considerations in production. Working knowledge of Databricks is a huge plus. How You’ll Grow At HCLTech, we offer continuous opportunities for you to find your spark and grow with us. We want you to be happy and satisfied with your role and to really learn what type of work sparks your brilliance the best. Throughout your time with us, we offer transparent communication with senior-level employees, learning and career development programs at every level, and opportunities to experiment in different roles or even pivot industries. We believe that you should be in control of your career with unlimited opportunities to find the role that fits you best.

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 Description Oracle Cloud Infrastructure (OCI) is a strategic growth area for Oracle. It is a comprehensive cloud service offering in the enterprise software industry, spanning Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). OCI is currently building a future-ready Gen2 cloud Data Science service platform. At the core of this platform, lies Cloud AI Cloud Service. What OCI AI Cloud Services are: A set of services on the public cloud, that are powered by ML and AI to meet the Enterprise modernization needs, and that work out of the box. These services and models can be easily specialized for specific customers/domains by demonstrating existing OCI services. Key Points: Enables customers to add AI capabilities to their Apps and Workflows easily via APIs or Containers, Useable without needing to build AI expertise in-house and Covers key gaps – Decision Support, NLP, for Public Clouds and Enterprise in NLU, NLP, Vision and Conversational AI. You’re Opportunity: As we innovate to provide a single collaborative ML environment for data-science professionals, we will be extremely happy to have you join us and share the very future of our Machine Learning platform - by building an AI Cloud service. We are addressing exciting challenges at the intersection of artificial intelligence and innovative cloud infrastructure. We are building cloud services in Computer vision for Image/Video and Document Analysis, Decision Support (Anomaly Detection, Time series forecasting, Fraud detection, Content moderation, Risk prevention, predictive analytics), Natural Language Processing (NLP), and, Speech that works out of the box for enterprises. Our product vision includes the ability for enterprises to be able to customize the services for their business and train them to specialize in their data by creating micro models that enhance the global AI models. What You’ll Do Develop scalable infrastructure, including microservices and a backend, that automates training, deployment, and optimization of ML model inference. Building a core of Artificial Intelligence and AI services such as Vision, Speech, Language, Decision, and others. Brainstorm and design various POCs using AI Perpetual AI Services for new or existing enterprise problems. Collaborate with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively communicating your needs, understanding theirs, and addressing external and internal shareholder product challenges. Lead research and development efforts to explore new tools, frameworks, and methodologies to improve backend development processes. Experiment with ML models in Python/C++ using machine learning libraries (Pytorch, ONNX, TensorRT, Triton, TensorFlow, Jax), etc. Leverage Cloud technology – Oracle Cloud (OCI), AWS, GCP, Azure, or similar technology. Qualifications Master’s degree or equivalent experience (preferred) in computer science, Statistics or Mathematics, artificial intelligence, machine learning, Computer vision, operations research, or related technical field. 3+ years for PhD or equivalent experience, 5+ years for Masters, or demonstrated ability designing, implementing, and deploying machine learning models in production environments. Practical experience in design, implementation, and production deployment of distributed systems using microservices architecture and APIs using common frameworks like Spring Boot (Java), etc. Practical experience working in a cloud environment: Oracle Cloud (OCI), AWS, GCP, Azure, and containerization (Docker, Kubernetes). Working knowledge of current techniques, approaches, and inference optimization strategies in machine learning models. Experience with performance tuning, scalability, and load balancing techniques. Expert in at least one high-level language such as Java/C++ (Java preferred). Expert in at least one scripting language such as Python, Javascript, and Shell . Deep understanding of data structures, and algorithms, and excellent problem-solving skills. Experience or willingness to learn and work in Agile and iterative development and DevOps processes. Strong drive to learn and master new technologies and techniques. You enjoy a fast-paced work environment. Additional Preferred Qualifications Experience with Cloud Native Frameworks tools and products is a plus Experience in Computer vision tasks like Image Classification, Object Detection, Segmentation, Text detection & recognition, Information extraction from documents, etc. Having an impressive set of GitHub projects or contributions to open-source technologies is a plus Hands-on experience with horizontally scalable data stores such as Hadoop and other NoSQL technologies like Cassandra is a plus. Our vision is to provide an immersive AI experience on Oracle Cloud. Aggressive as it might sound, our growth journey is fueled by highly energetic, technology-savvy engineers like YOU who are looking to grow with us to meet the demands of building a powerful next-generation platform. Are you ready to do something big? Career Level - IC3 About Us As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.

Job Description Must Have Skills: Extensive knowledge of large language models, natural language processing techniques and prompt engineering. Experience in testing and validation processes to ensure the models' accuracy and efficiency in real-world scenarios. Experience in design, build, and deployment of innovative applications utilizing Gen AI technologies such as RAG (Retrieval-Augmented Generation) based chatbots or AI Agents. Proficiency in programming using Python or Java. Familiarity with Oracle Cloud Infrastructure or similar cloud platforms. Effective communication and presentation skills. Analyzes problems, identifies solutions, and makes decisions. Demonstrates a willingness to learn, adapt, and grow professionally. Good to Have Skills: Experience in LLM architectures, model evaluation, and fine-tuning techniques. Hands-on experience with emerging LLM frameworks and plugins, such as LangChain, LlamaIndex, VectorStores and Retrievers, TensorFlow, PyTorch, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc. Proficiency in databases (e.g., Oracle, MySQL), developing and executing AI over any of the cloud data platforms, associated data stores, Graph Stores, Vector Stores and pipelines. Understanding of the security and compliance requirements for ML/GenAI implementations. Career Level - IC2/IC3 Responsibilities As a member of Oracle Cloud LIFT, you’ll help guide our customers from concept to successful cloud deployment. You’ll: Shape architecture and solution design with best practices and experience. Own the delivery of agreed workload implementations. Validate and test deployed solutions. Conduct security assurance reviews. You’ll work in a fast-paced, international environment, engaging with customers across industries and regions. You’ll collaborate with peers, sales, architects, and consulting teams to make cloud transformation real. https://www.oracle.com/in/cloud/cloud-lift/ Qualifications Career Level - IC2 About Us As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.

Introduction IBM is a global technology and innovation company. It is the largest technology and consulting employer in the world, with presence in 170 countries. The diversity and breadth of the entire IBM portfolio of research, consulting, solutions, services, systems and software, uniquely distinguishes IBM from other companies in the industry. Over the past 100 years, a lot has changed at IBM, in this new era of Cognitive Business, IBM is helping to reshape industries as diverse as healthcare, retail, banking, travel, manufacturing, and many more, by bringing together our expertise in Cloud, Analytics, Security, Mobile, and the Internet of Things. We like to say, "be essential." We are changing how we create. How we collaborate. How we analyze. How we engage. IBM is a leader in this global transformation. Join the next generation of innovators, inventors and entrepreneurs who are changing the very way the world works. We want the brightest minds doing work that inspires, in an environment where growth is encouraged. IBMers get to discover their potential, so they’re inspired to create breakthroughs that help our clients succeed. We’re building diverse teams with people who want their ideas to matter. Join us — you’ll be proud to call yourself an IBMer. Your Role And Responsibilities Back end development with GoLang Expertise in Kubernetes/OpenShift, Cloud service providers. Knowledge of Generative AI, and ability to integrate AI to applications. Ability to pick up new areas based on business requirements Excellent communication skills Required Technical And Professional Expertise 6+ years of overall experience in backend development. Excellent understanding of system design and best practices. 6+ years of application development with GoLang development. Good level of expertise in Kubernetes or OpenShift, use of Docker/Podman and Cloud service providers. Good level of knowledge of CNI, container native storage. Expertise in Version Control - Git Experience using cloud technologies (AWS/GCP/Azure/IBM Cloud) Experience with Ansible and Shell scripting Proficient in Linux administration. Experience of IaC (Terraform) Expertise in Version Control - Git Design functional DevOps application lifecycle. Good understanding of CICD pipelines such as Jenkins. Should have hands-on in writing and debugging Jenkinsfile Experience using build tools such as Maven, Gradle, Make, Ant Knowledge of AI - Pytorch, TensorFlow, Scikit, Generative AI, and ability to integrate AI functionalities to applications.

Job Description Must Have Skills: Extensive knowledge of large language models, natural language processing techniques and prompt engineering. Experience in testing and validation processes to ensure the models' accuracy and efficiency in real-world scenarios. Experience in design, build, and deployment of innovative applications utilizing Gen AI technologies such as RAG (Retrieval-Augmented Generation) based chatbots or AI Agents. Proficiency in programming using Python or Java. Familiarity with Oracle Cloud Infrastructure or similar cloud platforms. Effective communication and presentation skills. Analyzes problems, identifies solutions, and makes decisions. Demonstrates a willingness to learn, adapt, and grow professionally. Good to Have Skills: Experience in LLM architectures, model evaluation, and fine-tuning techniques. Hands-on experience with emerging LLM frameworks and plugins, such as LangChain, LlamaIndex, VectorStores and Retrievers, TensorFlow, PyTorch, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc. Proficiency in databases (e.g., Oracle, MySQL), developing and executing AI over any of the cloud data platforms, associated data stores, Graph Stores, Vector Stores and pipelines. Understanding of the security and compliance requirements for ML/GenAI implementations. Career Level - IC2/IC3 Responsibilities As a member of Oracle Cloud LIFT, you’ll help guide our customers from concept to successful cloud deployment. You’ll: Shape architecture and solution design with best practices and experience. Own the delivery of agreed workload implementations. Validate and test deployed solutions. Conduct security assurance reviews. You’ll work in a fast-paced, international environment, engaging with customers across industries and regions. You’ll collaborate with peers, sales, architects, and consulting teams to make cloud transformation real. https://www.oracle.com/in/cloud/cloud-lift/ Qualifications Career Level - IC2 About Us As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.

🚀 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.

🧠 Job Title: Senior Machine Learning Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 4–8 years Education : B.Tech / M.Tech / Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or related fields 🚀 About Darwix AI Darwix AI is India's fastest-growing GenAI SaaS startup, building real-time conversational intelligence and agent-assist platforms that supercharge omnichannel enterprise sales teams across India, MENA, and Southeast Asia. Our mission is to redefine how revenue teams operate by using Generative AI, LLMs, Voice AI , and deep analytics to deliver better conversations, faster deal cycles, and consistent growth. Our flagship platform, Transform+ , analyzes millions of hours of sales conversations, gives live nudges, builds AI-powered sales content, and enables revenue teams to become truly data-driven — in real time. We’re backed by marquee investors, industry veterans, and AI experts, and we’re expanding fast. As a Senior Machine Learning Engineer , you will play a pivotal role in designing and deploying intelligent ML systems that power every layer of this platform — from speech-to-text, diarization, vector search, and summarization to recommendation engines and personalized insights. 🎯 Role Overview This is a high-impact, high-ownership role for someone who lives and breathes data, models, and real-world machine learning. You will design, train, fine-tune, deploy, and optimize ML models across various domains — speech, NLP, tabular, and ranking. Your work will directly power critical product features: from personalized agent nudges and conversation scoring to lead scoring, smart recommendations, and retrieval-augmented generation (RAG) pipelines. You’ll be the bridge between data science, engineering, and product — converting ideas into models, and models into production-scale systems with tangible business value. 🧪 Key Responsibilities🔬 1. Model Design, Training, and Optimization Develop and fine-tune machine learning models using structured, unstructured, and semi-structured data sources. Work with models across domains: text classification, speech transcription, named entity recognition, topic modeling, summarization, time series, and recommendation systems. Explore and implement transformer architectures, BERT-style encoders, Siamese networks, and retrieval-based models. 📊 2. Data Engineering & Feature Extraction Build robust ETL pipelines to clean, label, and enrich data for supervised and unsupervised learning tasks. Work with multimodal inputs — audio, text, metadata — and build smart representations for downstream tasks. Automate data collection from APIs, CRMs, sales transcripts, and call logs. ⚙️ 3. Productionizing ML Pipelines Package and deploy models in scalable APIs (using FastAPI, Flask, or similar frameworks). Work closely with DevOps to containerize and orchestrate ML workflows using Docker, Kubernetes, or CI/CD pipelines. Ensure production readiness: logging, monitoring, rollback, and fail-safes. 📈 4. Experimentation & Evaluation Design rigorous experiments using A/B tests, offline metrics, and post-deployment feedback loops. Continuously optimize model performance (latency, accuracy, precision-recall trade-offs). Implement drift detection and re-training pipelines for models in production. 🔁 5. Collaboration with Product & Engineering Translate business problems into ML problems and align modeling goals with user outcomes. Partner with product managers, AI researchers, data annotators, and frontend/backend engineers to build and launch features. Contribute to the product roadmap with ML-driven ideas and prototypes. 🛠️ 6. Innovation & Technical Leadership Evaluate open-source and proprietary LLM APIs, AutoML frameworks, vector databases, and model inference techniques. Drive innovation in voice-to-insight systems (ASR + Diarization + NLP). Mentor junior engineers and contribute to best practices in ML development and deployment. 🧰 Tech Stack🔧 Languages & Frameworks Python (core), SQL, Bash PyTorch, TensorFlow, HuggingFace, scikit-learn, XGBoost, LightGBM 🧠 ML & AI Ecosystem Transformers, RNNs, CNNs, CRFs BERT, RoBERTa, GPT-style models OpenAI API, Cohere, LLaMA, Mistral, Anthropic Claude FAISS, Pinecone, Qdrant, LlamaIndex ☁️ Deployment & Infrastructure Docker, Kubernetes, GitHub Actions, Jenkins AWS (EC2, Lambda, S3, SageMaker), GCP, Azure Redis, PostgreSQL, MongoDB 📊 Monitoring & Experimentation MLflow, Weights & Biases, TensorBoard, Prometheus, Grafana 👨‍💼 Qualifications🎓 Education Bachelor’s or Master’s degree in CS, AI, Statistics, or related quantitative disciplines. Certifications in advanced ML, data science, or AI are a plus. 🧑‍💻 Experience 4–8 years of hands-on experience in applied machine learning. Demonstrated success in deploying models to production at scale. Deep familiarity with transformer-based architectures and model evaluation. ✅ You’ll Excel In This Role If You… Thrive on solving end-to-end ML problems — not just notebooks, but deployment, testing, and iteration. Obsess over clean, maintainable, reusable code and pipelines. Think from first principles and challenge model assumptions when they don’t work. Are deeply curious and have built multiple projects just because you wanted to know how something works. Are comfortable working with ambiguity, fast timelines, and real-time data challenges. Want to build AI products that get used by real people and drive revenue outcomes — not just vanity demos. 💼 What You’ll Get at Darwix AI Work with some of the brightest minds in AI , product, and design. Solve AI problems that push the boundaries of real-time, voice-first, multilingual enterprise use cases. Direct mentorship from senior architects and AI scientists. Competitive compensation (₹30L–₹45L CTC) + ESOPs + rapid growth trajectory. Opportunity to shape the future of a global-first AI startup built from India. Hands-on experience with the most advanced tech stack in applied ML and production AI. Front-row seat to a generational company that is redefining enterprise AI. 📩 How to Apply Ready to build with us? Send your resume, GitHub/portfolio, and a short write-up on: “What’s the most interesting ML system you’ve built — and what made it work?” Email: people@darwix.ai Subject: Senior ML Engineer – Application 🔐 Final Notes We value speed, honesty, and humility. We ship fast, fail fast, and learn even faster. This role is designed for high-agency, hands-on ML engineers who want to make a difference — not just write code. If you’re looking for a role where you own real impact , push technical boundaries, and work with a team that’s as obsessed with AI as you are — then Darwix AI is the place for you. Darwix AI – GenAI for Revenue Teams. Built from India, for the World.

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Senior Data Scientist Location: Bangalore Reporting to: Senior Manager Analytics Purpose of the role We seek a highly skilled Senior Machine Learning Engineer / Senior Data Scientist to design, develop, and deploy advanced machine learning models and systems. The ideal candidate will have deep expertise in machine learning algorithms, data processing, and model deployment, with a proven track record of delivering scalable AI solutions in production environments. This role requires strong technical leadership, collaboration with cross-functional teams, and a passion for solving complex problems. Key tasks & accountabilities Model Development: Design, develop, and optimize machine learning models for various applications, including but not limited to natural language processing, computer vision, and predictive analytics. Data Pipeline Management: Build and maintain robust data pipelines for preprocessing, feature engineering, and data augmentation to support model training and evaluation. Model Deployment: Deploy machine learning models into production environments, ensuring scalability, reliability, and performance using tools like Docker, Kubernetes, or cloud platforms preferably Azure. Research and Innovation: Stay updated on the latest advancements in machine learning and AI, incorporating state-of-the-art techniques into projects to improve performance and efficiency. Collaboration: Work closely with data scientists, software engineers, product managers, and other stakeholders to translate business requirements into technical solutions. Performance Optimization: Monitor and optimize model performance, addressing issues like model drift, bias, and scalability challenges. Code Quality: Write clean, maintainable, and well-documented code, adhering to best practices for software development and version control (e.g., Git). Mentorship: Provide technical guidance and mentorship to junior engineers, fostering a culture of learning and innovation within the team. Qualifications, Experience, Skills Level Of Educational Attainment Required Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field. PhD is a plus. Previous Work Experience 5+ years of experience in machine learning, data science, or a related field. Proven experience in designing, training, and deploying machine learning models in production. Hands-on experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). Technical Skills Required Proficiency in Python and libraries/frameworks such as TensorFlow, PyTorch, Scikit-learn, or Hugging Face. Strong understanding of machine learning algorithms (e.g., regression, classification, clustering, deep learning, reinforcement learning, optimization). Experience with big data technologies (e.g., Hadoop, Spark, or similar) and data processing pipelines. Familiarity with MLOps practices, including model versioning, monitoring, and CI/CD for ML workflows. Knowledge of software engineering principles, including object-oriented programming, API development, and microservices architecture. Other Skills Required Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Ability to work in a fast-paced, dynamic environment and manage multiple priorities. Experience with generative AI models or large language models (LLMs). Familiarity with distributed computing or high-performance computing environments. And above all of this, an undying love for beer! We dream big to create future with more cheers

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Junior Data Scientist Location: Bangalore Reporting to: Senior Manager – Analytics Purpose of the role The Global GenAI Team at Anheuser-Busch InBev (AB InBev) is tasked with constructing competitive solutions utilizing GenAI techniques. These solutions aim to extract contextual insights and meaningful information from our enterprise data assets. The derived data-driven insights play a pivotal role in empowering our business users to make well-informed decisions regarding their respective products. In the role of a Machine Learning Engineer (MLE), you will operate at the intersection of: LLM-based frameworks, tools, and technologies Cloud-native technologies and solutions Microservices-based software architecture and design patterns As an additional responsibility, you will be involved in the complete development cycle of new product features, encompassing tasks such as the development and deployment of new models integrated into production systems. Furthermore, you will have the opportunity to critically assess and influence the product engineering, design, architecture, and technology stack across multiple products, extending beyond your immediate focus. Key tasks & accountabilities Large Language Models (LLM): Experience with LangChain, LangGraph Proficiency in building agentic patterns like ReAct, ReWoo, LLMCompiler Multi-modal Retrieval-Augmented Generation (RAG): Expertise in multi-modal AI systems (text, images, audio, video) Designing and optimizing chunking strategies and clustering for large data processing Streaming & Real-time Processing: Experience in audio/video streaming and real-time data pipelines Low-latency inference and deployment architectures NL2SQL: Natural language-driven SQL generation for databases Experience with natural language interfaces to databases and query optimization API Development: Building scalable APIs with FastAPI for AI model serving Containerization & Orchestration: Proficient with Docker for containerized AI services Experience with orchestration tools for deploying and managing services Data Processing & Pipelines: Experience with chunking strategies for efficient document processing Building data pipelines to handle large-scale data for AI model training and inference AI Frameworks & Tools: Experience with AI/ML frameworks like TensorFlow, PyTorch Proficiency in LangChain, LangGraph, and other LLM-related technologies Prompt Engineering: Expertise in advanced prompting techniques like Chain of Thought (CoT) prompting, LLM Judge, and self-reflection prompting Experience with prompt compression and optimization using tools like LLMLingua, AdaFlow, TextGrad, and DSPy Strong understanding of context window management and optimizing prompts for performance and efficiency Qualifications, Experience, Skills Level of educational attainment required (1 or more of the following) Bachelor's or masterʼs degree in Computer Science, Engineering, or a related field. Previous Work Experience Required Proven experience of 1+ years in developing and deploying applications utilizing Azure OpenAI and Redis as a vector database. Technical Skills Required Solid understanding of language model technologies, including LangChain, OpenAI Python SDK, LammaIndex, OLamma, etc. Proficiency in implementing and optimizing machine learning models for natural language processing. Experience with observability tools such as mlflow, langsmith, langfuse, weight and bias, etc. Strong programming skills in languages such as Python and proficiency in relevant frameworks. Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes). And above all of this, an undying love for beer! We dream big to create future with more cheer

Position Overview We are hiring a Lead AI Data Scientist to join our client's Ahmedabad-based team. Collaborating closely with our leadership, you'll develop innovative applications and structured processes that enhance productivity and expand market reach. Key Responsibilities Lead the development of sophisticated machine learning and deep learning models that solve complex business problems. Manage timelines, scope, and deliverables for AI/data science projects, ensuring projects are completed on time and meet quality standards. Design and implement machine learning models and AI applications tailored for internal and customer-focused solutions. Perform XML regression analysis and build robust C++ pipelines for data processing. Continuously optimize models for performance, accuracy, and scalability, considering real-world constraints such as latency and interpretability. Develop tools to optimize personal and company-wide productivity. Collaborate with cross-functional teams to identify automation opportunities. Oversee the data pipeline and infrastructure, ensuring data quality, consistency, and accessibility for model development. Analyze complex data sets to provide actionable insights. Participate in strategic brainstorming sessions to align AI initiatives with the company’s vision. Qualifications Bachelor’s or master’s degree in data science, Computer Science, or a related field. Expertise in XML regression analysis and C++ programming. Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch). Strong problem-solving and analytical skills. Passion for AI and belief in the transformative power of systems and processes. Proactive attitude and excellent communication skills. Benefits Opportunity to work on groundbreaking AI technologies. Collaborative, innovative, and supportive work environment. Competitive salary and benefits package. Career growth opportunities in a fast-growing company. Skills: data science,c++ programming,data analysis,data pipeline management,xml regression analysis,pytorch,machine learning,tensorflow,deep learning,c++

Responsibilities: Analyze business needs and translate them into technical and functional requirements, with a focus on AI-based tools and features . Collaborate with cross-functional teams (Product, Development, Marketing, QA) to develop AI-powered fintech solutions. Understand AI algorithms at the application level to propose realistic, value-driven enhancements. Prepare wireframes, flowcharts, use cases, and user stories that incorporate AI-driven features or automation logic. Facilitate discussions between business teams and developers to ensure clear alignment on goals. Assist in data analysis, model validation inputs, and AI tool integration within products. Coordinate with QA for UAT and ensure product deliverables meet business objectives. Keep up-to-date with the latest AI trends, tools (e.g., NLP, ML, chatbots), and fintech compliance regulations. Requirements: Bachelor’s degree in Computer Science, Information Technology, Business Administration, or a related field. 1-2 years of experience as an IT Business Analyst in a tech or AI/ML-driven environment. Strong understanding of AI applications , data-driven solutions, and modern AI tools/platforms (e.g., ChatGPT, TensorFlow, Azure AI, Google AI tools). Experience working in Agile/Scrum environments and using tools like JIRA, Confluence, Figma, etc. Excellent communication and stakeholder management skills. Ability to simplify technical AI concepts for business users. Job Types: Full-time, Permanent Pay: From ₹200,000.00 per year Benefits: Commuter assistance Flexible schedule Leave encashment Life insurance Provident Fund Ability to commute/relocate: Manjeri, Kerala: Reliably commute or planning to relocate before starting work (Required) Shift availability: Day Shift (Required) Night Shift (Required) Work Location: In person

Enterprise Architect (LLMs, GenAI, AI/ML) Experience: 12+ years Location: India Note: This role requires flexibility to travel or relocate to Abu Dhabi (UAE) for onsite client requirements (typically 2 to 3 months at a time). About the Role NorthBay Solutions seeks an Enterprise Architect with proven GenAI leadership, strong AI/ML foundation, and solid enterprise architecture background. We want seasoned professionals with deployment experience across on-premises, cloud, and hybrid environments. Core Responsibilities Design end-to-end AI-powered enterprise solutions integrating traditional systems with AI/ML Lead 8–12 engineers across full-stack, DevOps, and AI/ML specializations in Agile environments Drive technical decisions spanning infrastructure, databases, APIs, microservices, and AI components Technical Requirements GenAI Leadership (3+ Years) – PRIMARY Expert-level LLM experience (LLAMA, Mistral, GPT) including fine-tuning and deployment Agentic AI, MultiAgent systems, Agentic RAG implementations Vector Databases, LangChain, Langraph, and modern GenAI toolchains Advanced prompt engineering and Chain-of-Thought techniques 3+ production GenAI applications successfully implemented AI/ML Foundation (4–5 Years) Hands-on AI/ML experience building production systems with Python, TensorFlow, PyTorch ML model lifecycle management from development to deployment and monitoring Integration of AI/ML models with existing enterprise architectures Enterprise Architecture & Deployment (8+ Years) Full-stack development with MERN stack or equivalent Deployment experience across on-premises, cloud, and hybrid environments Kubernetes expertise for container orchestration and deployment Database proficiency: SQL (PostgreSQL/MySQL) and NoSQL (MongoDB/DynamoDB) API development: RESTful services, GraphQL, microservices architecture DevOps experience: Docker, CI/CD pipelines, infrastructure automation Cloud & Infrastructure Strong cloud experience (AWS/Azure/GCP) with ML services AWS: SageMaker, Bedrock, Lambda, API Gateway or equivalent Hybrid architecture design combining on-prem, cloud, and AI/ML systems Proven Delivery 7+ complex projects delivered across enterprise systems and AI/ML solutions Team leadership experience managing diverse technical teams Requirements (Good to have) AWS/Azure/GCP certifications (Solutions Architect + ML Specialty preferred) Strong communication skills bridging business and technical requirements Agile/Scrum leadership experience with measurable team performance improvements Ideal Candidate Priority expertise: GenAI Leadership AI/ML Foundation Enterprise Architecture with deployment experience across on-premises, cloud, and hybrid environments. h3qtfPMab1

Tezo is a new generation Digital & AI solutions provider, with a history of creating remarkable outcomes for our customers. We bring exceptional experiences using cutting-edge analytics, data proficiency, technology, and digital excellence. We are seeking a highly experienced and dynamic Practice Head – Data Science & AI to lead our data practice in Hyderabad. This role is ideal for a technology leader with a strong foundation in Data Science, Artificial Intelligence (AI), and Machine Learning (ML), along with proven experience in building and scaling data practices. The ideal candidate will also have a strong business acumen with experience in solution selling and pre-sales. Key Responsibilities: Leadership & Strategy: Define and drive the strategic vision for the Data Science and AI practice. Build, lead, and mentor a high-performing team of data scientists, ML engineers, and AI experts. Collaborate with cross-functional teams to integrate data-driven solutions into broader business strategies. Technical Expertise: Lead the design and delivery of advanced AI/ML solutions across various domains. Stay abreast of industry trends, emerging technologies, and best practices in AI, ML, and data science. Provide technical guidance and hands-on support as needed for key initiatives. Practice Development: Establish frameworks, methodologies, and best practices to scale the data science practice. Define and implement reusable components, accelerators, and IPs for efficient solution delivery. Client Engagement & Pre-Sales: Support business development by working closely with sales teams in identifying opportunities, creating proposals, and delivering presentations. Engage in solution selling by understanding client needs and proposing tailored AI/ML-based solutions. Build strong relationships with clients and act as a trusted advisor on their data journey. Required Skills & Experience: 12+ years of overall experience with at least 5+ years in leading data science/AI teams. Proven experience in setting up or leading a data science or AI practice. Strong hands-on technical background in AI, ML, NLP, predictive analytics, and data engineering. Experience with tools and platforms like Python, R, TensorFlow, PyTorch, Azure ML, AWS SageMaker, etc. Strong understanding of data strategy, governance, and architecture. Demonstrated success in solutioning and pre-sales engagements. Excellent communication, leadership, and stakeholder management skills.

About US: - Headquartered in the Silicon Valley with offices in London, Hyderabad and Singapore, Accellor is a Microsoft Gold Partner and a premier Salesforce Partner that uses best-of-breed Cloud technology to deliver superior customer engagement and business effectiveness for clients. We bring a deep understanding of Financial, Retail, High Tech, Healthcare, and Retail industries, rolling out end-to-end implementation of salesforce.com and powerful third-party apps. We also build products that are sold on the AppExchange and used by both boutique businesses and Fortune 500 companies. Majority of our team members based at Hyderabad, delivering best of breed cloud solutions to customers in the US, UK and APAC region. We’ve created an atmosphere that encourages curiosity, constant learning, and persistence. We encourage our employees to grow and explore their interests. We cultivate an environment of collaboration, autonomy and delegation – we know our people have a strong work ethic and a sense of pride and ownership over their work. They are passionate, eager, and motivated – focused on building the perfect solution but never losing sight of the bigger picture. We are looking for a highly motivated and skilled AI/ML Engineer to join our dynamic team. As an AI/ML Engineer, you will be responsible for designing, developing, and deploying cutting-edge AI and machine learning solutions to solve complex business problems. You will collaborate with cross-functional teams to identify opportunities for AI/ML integration and work on developing scalable and efficient algorithms. The ideal candidate should possess a strong background in machine learning, programming, and data analysis, along with a passion for staying up-to-date with the latest advancements in the field of AI. Responsibilities: Design, develop, and implement AI/ML models and algorithms to solve specific business problems. Collaborate with stakeholders to understand business requirements that can be addressed using AI and machine learning techniques and to integrate AI/ML solutions into production systems and applications. Pre-process, clean, and analyse large datasets to extract meaningful insights and features for model training. Optimize and fine-tune models for accuracy, performance, and scalability. Stay updated with the latest research and advancements in AI/ML, and incorporate relevant techniques into the development process. Evaluate and test models using appropriate evaluation metrics to ensure their effectiveness and robustness. Monitor and maintain deployed models, making necessary updates and improvements as needed. Participate in code reviews, knowledge sharing, and mentoring of junior team members. Document methodologies, experiments, and results clearly and effectively. Continuously iterate and improve AI/ML solutions based on feedback and real-world performance. Requirements 3-5 years of relevant experience in data pre-processing, feature engineering, and model evaluation. Bachelor's/Master's degree in Computer Science Engineering. Solid understanding of machine learning algorithms, statistics, and data structures. Proficiency in programming languages such as Python, Java/R and familiarity with libraries like TensorFlow, PyTorch, Scikit-learn, etc. Strong problem-solving skills and ability to think critically about complex challenges. Familiarity with cloud platforms and tools (ex: Azure/AWS/GCP) for model deployment and management. Experience in deploying machine learning models in production environments is a plus. Excellent communication skills to convey technical concepts to both technical and non-technical stakeholders. Strong teamwork and collaboration skills. Continuous learning attitude to keep up with the rapidly evolving AI/ML landscape. Experience with version control systems like Git and Copilot is a plus. At Accellor, we foster a collaborative and innovative environment where creativity and diverse perspectives are valued. We are committed to pushing the boundaries of technology and delivering solutions that make a meaningful impact. Join our team and be part of shaping the future with AI and Machine learning. Benefits Exciting Projects: We focus on industries like High-Tech, communication, media, healthcare, retail and telecom. Our customer list is full of fantastic global brands and leaders who love what we build for them. Collaborative Environment: You Can expand your skills by collaborating with a diverse team of highly talented people in an open, laidback environment — or even abroad in one of our global centres. Work-Life Balance: Accellor prioritizes work-life balance, which is why we offer flexible work schedules, opportunities to work from home, and paid time off and holidays. Professional Development: Our dedicated Learning & Development team regularly organizes Communication skills training, Stress Management program, professional certifications, and technical and soft skill trainings. Excellent Benefits: We provide our employees with competitive salaries, family medical insurance, Personal Accident Insurance, Periodic health awareness program, extended maternity leave, annual performance bonuses, and referral bonuses. Disclaimer: - Accellor is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic

The people here at Apple don’t just build products - we craft the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that supports the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. The Global Business Intelligence team provides data services, analytics, reporting, and data science solutions to Apple’s business groups, including Retail, iTunes, Marketing, AppleCare, Operations, Finance, and Sales. These solutions are built on top of an end-to-end machine learning platform with sophisticated AI capabilities. We are looking for a competent, experienced, and driven machine learning engineer to define and build some of the best-in-class machine learning solutions and tools for Apple. Description As a Machine Learning Engineer, you will work on building intelligent systems to democratize AI across a wide range of solutions within Apple. You will drive the development and deployment of innovative AI models and systems that directly impact the capabilities and performance of Apple’s products and services. You will implement robust, scalable ML infrastructure, including data storage, processing, and model serving components, to support seamless integration of AI/ML models into production environments. You will develop novel feature engineering, data augmentation, prompt engineering and fine-tuning frameworks that achieve optimal performance on specific tasks and domains. You will design and implement automated ML pipelines for data preprocessing, feature engineering, model training, hyper-parameter tuning, and model evaluation, enabling rapid experimentation and iteration. You will also implement advanced model compression and optimization techniques to reduce the resource footprint of language models while preserving their performance. Have continuous focus to Brainstorm and Design various POCs using AI/ML Services for new or existing enterprise problems. YOU SHOULD BE ABLE TO: - Understand a business challenge - Collaborate with business and other multi-functional teams - Design a statistical or deep learning solution to find the needed answer to it. - Develop it by yourself or guide another person to do it. - Deliver the outcome into production, (v) Keep a good governance of your work. There are meaningful opportunities for you deliver impactful influences to Apple. Key Qualifications 4+ years of ML engineering experience in feature engineering, model training, model serving, model monitoring and model refresh management Experience developing AI/ML systems at scale in production or in high-impact research environments Passionate about computer vision, natural language processing, especially in LLMs and Generative AI systems Knowledge with the common frameworks and tools such as PyPorch or TensorFlow Experience with transformer models such as BERT, GPT etc. and understanding of their underlying principles is a plus Strong coding, analytical, software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment Experience in handling performance, application and security log management Applied knowledge of statistical data analysis, predictive modeling classification, Time Series techniques, sampling methods, multivariate analysis, hypothesis testing, and drift analysis. Proficiency in programming languages and tools like Python, R, Git, Airflow, Notebooks. Experience with data visualization tools like matplotlib, d3.js., Tableau would be a plus Education & Experience Bachelor’s Degree or Equivalent experience Submit CV

We are seeking a Data Engineer with 1–2 years of hands-on experience to join our technology team. The ideal candidate will focus on building efficient data infrastructure and delivering robust solutions for machine learning and computer vision initiatives. The role offers opportunities to collaborate with diverse teams and engage with state-of-the-art technology. Key Responsibilities Design, implement, and maintain data pipelines using Python. Develop, train, and optimize computer vision models —including deep learning architectures, OCR (Optical Character Recognition), and object detection frameworks like YOLO . Utilize Python for data engineering, scripting, and machine learning workflows. Build models with TensorFlow and PyTorch for advanced analytics and deep learning solutions. Containerize and deploy applications using Docker . Manage and maintain AWS infrastructure , ensuring scalable and reliable deployment of solutions. Collaborate with stakeholders to enable seamless data flow and integration. Apply best practices for code versioning, documentation, and reproducibility. Required Skills and Experience (Must-Have) Python: Strong skills in programming and scripting for data workflows and machine learning. Computer Vision: Practical experience creating and deploying computer vision models, including object detection and OCR. YOLO: Hands-on experience with YOLO for real-time object detection projects. 1–2 years proven experience working in a Data Engineer or similar data-centric role. Familiarity with TensorFlow and PyTorch. Experience with Docker for containerized workloads. Working knowledge of AWS services (EC2, S3, etc.) for cloud-based deployments. Strong teamwork and communication abilities. Good-to-Have (Preferred Skills) Experience with Grafana for monitoring and visualizing metrics. Experience integrating with GRPC. Bachelor’s degree in Computer Science, Data Engineering, or a related field. Exposure to CI/CD pipelines, serverless architectures, or data versioning tools. Understanding of cloud and data security best practices. Experience in agile development environments. What We Offer Projects utilizing the latest in AI, computer vision, and data engineering. Collaborative, growth-oriented work culture. Flexible work options and ongoing learning opportunities. Competitive compensation and benefits. Job Type: Full-time Pay: ₹20,000.00 - ₹30,000.00 per month Benefits: Health insurance Provident Fund Work Location: In person

QA Tester – Machine Learning Experience: 1–2 Years Location: Netaji Subhash Place, Delhi Employment Type: Full-time Job Summary: We are looking for a passionate and detail-oriented QA Tester with 1–2 years of experience to join our AI team. In this role, you will work closely with AI-ML engineers and software developers to ensure the quality and reliability of ML models, data pipelines, and model-integrated applications. Key Responsibilities: Design, develop, and execute test plans and test cases for ML models and data pipelines. Validate model outputs against ground truth datasets, with a focus on evaluating classification performance metrics like accuracy, precision, recall, F1-score, and ROC-AUC. Perform functional, regression, and integration testing for applications incorporating ML models. Collaborate with ML engineers to ensure testability and performance of models. Write scripts to automate model testing and data validation. Identify, record, document, and track bugs and model anomalies. Ensure data quality and consistency in training and inference pipelines. Test and validate APIs serving ML models in production. Contribute to continuous improvement of QA processes and tools. Required Skills & Qualifications: Bachelor’s degree in Computer Science, Engineering, or a related field. 1–2 years of experience in QA/testing roles, preferably in ML or data-heavy environments. Solid understanding of QA methodologies, tools, and processes. Experience in testing REST APIs and working with tools like Postman or Swagger. Basic knowledge of Python, with experience in test automation using PyTest or similar frameworks. Familiarity with ML concepts and Docker. Hands-on experience working with structured/unstructured datasets. Ability to write clear, concise, and comprehensive test cases and test reports. Preferred Qualifications: Experience with ML libraries like scikit-learn, TensorFlow, or PyTorch. Exposure to data annotation, labeling, or synthetic data generation tools. Familiarity with version control systems (e.g., Git) and CI/CD workflows. Knowledge of SQL or MongoDB for data validation. Understanding of data drift, model degradation, and ML lifecycle monitoring. Why Join Us? Work on real-world ML products with a measurable impact. Collaborate with a dynamic and skilled team. Opportunity to grow in both QA and ML domains. Flexible work environment and supportive culture. Job Type: Full-time Pay: ₹20,000.00 - ₹30,000.00 per month Benefits: Health insurance Provident Fund Work Location: In person Speak with the employer +91 8178295650

Overview Tricky WebSolutions is seeking a skilled and enthusiastic AI/ML Developer with at least 2 years of experience to join our innovative team. The successful candidate will be responsible for developing and deploying machine learning models, conducting data analysis, and collaborating with cross-functional teams to integrate AI solutions into our products and services. Responsibilities Model Development : Design, develop, and deploy machine learning models for various applications. Implement algorithms and conduct experiments to test and validate models. Optimize and improve the performance of existing models. Data Analysis : Collect, preprocess, and analyze large datasets to extract meaningful insights. Develop data pipelines and ensure data quality and integrity. Collaboration : Work closely with data scientists, software developers, and product managers to integrate AI solutions into web applications. Communicate findings and technical concepts to non-technical stakeholders. Research and Innovation : Stay updated with the latest advancements in AI and machine learning technologies. Explore and propose new techniques and tools to enhance AI capabilities. Deployment and Maintenance : Implement machine learning models in production environments. Monitor model performance and maintain AI systems. Requirements Educational Background : Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Technical Skills : Proficiency in programming languages such as Python or R. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of machine learning algorithms and principles. Familiarity with data preprocessing techniques and tools. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) is a plus. Analytical Skills : Strong problem-solving abilities and attention to detail. Ability to analyze complex data and interpret results. Communication Skills : Excellent written and verbal communication skills. Ability to explain technical concepts to a non-technical audience. Experience : At least 2 years of experience in AI/ML development or a related field. Experience with natural language processing (NLP) and computer vision is a plus. Experience in deploying machine learning models in production environments. Preferred Qualifications Certifications : Relevant certifications in AI/ML are advantageous. Project Management : Experience with agile methodologies and project management tools. Publications : Contributions to research papers or relevant publications in the field of AI/ML. How to Apply Interested candidates are invited to send their CV to hr@trickywebsolutions.com . Please include "AI/ML Developer Application" in the subject line of the email. Job Type: Full-time Pay: ₹10,000.00 - ₹40,000.00 per month Work Location: In person

Gain hands‑on experience with industry-relevant tasks—preprocessing real-world datasets, training and evaluating ML models using Python and libraries like TensorFlow or PyTorch, and deploying prototypes. Collaborate with engineering teams, document insights, and support deployment workflows in a production setting Job Type: Fresher Work Location: In person

Senior Consultant - Data Scientist Date: Jul 25, 2025 Location: Chennai, IN Requisition ID: 14612 Description: About Firstsource Firstsource Solutions Limited, an RP-Sanjiv Goenka Group company (NSE: FSL, BSE: 532809, Reuters: FISO.BO, Bloomberg: FSOL:IN), is a specialized global business process services partner, providing transformational solutions and services spanning the customer lifecycle across Healthcare, Banking and Financial Services, Communications, Media and Technology, Retail, and other diverse industries. With an established presence in the US, the UK, India, Mexico, Australia, South Africa, and the Philippines, we make it happen for our clients, solving their biggest challenges with hyper-focused, domain-centered teams and cutting-edge tech, data, and analytics. Our real-world practitioners work collaboratively to deliver future-focused outcomes. Position Summary: As a Data Scientist at FSL, you will leverage your expertise in Machine Learning, Deep Learning, Computer Vision, Natural Language Processing and Generative AI to develop innovative data-driven solutions and applications. You will play a key role in designing and deploying dynamic models and applications using modern web frameworks like Flask and FastAPI, ensuring efficient deployment and ongoing monitoring of these systems. Job Title: Sr. Consultant- Data Scientist Key Responsibilities: Model Development and Application: Design and implement advanced ML and DL models. Develop web applications for model deployment using Flask and FastAPI to enable real-time data processing and user interaction. Data Analysis: Perform exploratory data analysis to understand underlying patterns, correlations and trends. Develop comprehensive data processing pipelines to prepare large datasets for analysis and modeling. Generative AI: Employ Generative AI techniques to create new data points, enhance content generation and innovate within the field of synthetic data production. Collaborative Development: Work with cross-functional teams to integrate AI capabilities into products and systems. Ensure that all AI solutions are aligned with business goals and user needs. Research and Innovation: Stay updated with the latest developments in AI, ML, DL, CV and NLP. Explore new technologies and methodologies that can impact our products and services positively. Communication: Effectively communicate complex quantitative analysis in a clear, precise and actionable manner to senior management and other departments Required Skills and Qualifications: Education: BE or Master’s or PhD in Computer Science, Data Science, Statistics or a related field. Experience: 5 to 7 years of relevant experience in a data science role with a strong focus on ML, DL and statistical modeling. Technical Skills: Strong coding skills in Python, including experience with Flask or FastAPI. Proficiency in ML, DL frameworks (e.g., PyTorch, TensorFlow), CV (e.g., OpenCV) and NLP libraries (e.g., NLTK, spaCy). Generative AI: Experience with generative models such as GANs, VAEs or Transformers. Deployment Skills: Experience with Docker, Kubernetes and continuous integration/continuous deployment (CI/CD) pipelines. Strong Analytical Skills: Ability to translate complex data into actionable insights. Communication: Excellent written and verbal communication skills Certifications: Certifications in Data Science, ML or AI from recognized institutions is added advantage. ️ Disclaimer: Firstsource follows a fair, transparent, and merit-based hiring process. We never ask for money at any stage. Beware of fraudulent offers and always verify through our official channels or @firstsource.com email addresses.