1028 Inference Jobs - Page 36

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

Job description 🚀 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. 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

Responsibilities Design and implement Gen AI platform components, using Python (AI/ML)and modern microservices. Strong in Python and its associated Gen AI libraries Expert in Prompt engineering Strong understanding of Generative AI principles, including Large Language Models (LLM’s) and its implementation, RAG techniques, Fine tuning , inference etc Show more Show less

ML Engineer Experience: 4-7 Years Location: Bangalore Type: Full-time Responsibilities ● Model Development and Integration: Design, implement, test, integrate and deploy scalable machine learning models, integrating them into production systems and APIs to support existing and new customers. ● Experimentation and Optimization: Lead the design of experiments and hypothesis testing for product feature development; monitor and analyze model performance and data accuracy, making improvements as needed. ● Cross-Functional Collaboration: Work closely with cross-functional teams across India and the US to identify opportunities, deploy impactful solutions, and effectively communicate findings to both technical and non-technical stakeholders. ● Mentorship and Continuous Learning: Mentor junior team members, contribute to knowledge sharing, and stay current with best practices in data science, machine learning, and AI. Qualifications ● Education: Bachelors or Masters in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field. ●Experience: ○4-7 years of experience building and deploying machine learning models. ○Strong problem-solving skills with an emphasis on product development. ○Experience operating and troubleshooting scalable machine learning systems in the cloud. ●Technical Skills: ○ Programming and Frameworks: Proficient in Python with experience in TensorFlow, PyTorch, scikit-learn, and Pandas; familiarity with Golang is a plus; proficient with Git and collaborative workflows. ○ Software Engineering : Strong understanding of data structures, algorithms, and system design principles; experience in designing scalable, reliable, and maintainable systems. ○ Machine Learning Expertise: Extensive experience in AI and machine learning model development, including large language models, transformers, sequence models, causal inference, unsupervised clustering, and reinforcement learning. Knowledge of prompting techniques, embedding models and RAG. ○ Innovation in Machine Learning: Ability to design and conceive novel ways of problem solving using new machine learning models. ○ Integration, Deployment, and Cloud Services: Experience integrating machine learning models into backend systems and APIs; familiarity with Docker, Kubernetes, CI/CD tools, and Cloud Services like AWS/Azure/GCP for efficient deployment. ○ Data Management and Security: Proficient with SQL and experience with PostgreSQL; knowledge of NoSQL databases; understanding of application security and data protection principles. ●Methodologies and Tools: ○ Agile/Scrum Practices : Experience with Agile/Scrum methodologies. ○ Project Management Tools: Proficiency with Jira, Notion, or similar tools. ●Soft Skills: ○Excellent communication and problem-solving abilities. ○Ability to work independently and collaboratively. ○Strong organizational and time management skills. ○High degree of accountability and ownership. Nice-to-Haves ●Experience with big data tools like Hadoop or Spark. ●Familiarity with infrastructure management and operations lifecycle concepts. ●Experience working in a startup environment. ●Contributions to open-source projects or a strong GitHub portfolio. Show more Show less

Company Qualcomm India Private Limited Job Area Engineering Group, Engineering Group > Systems Engineering General Summary As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Systems Engineer, you will research, design, develop, simulate, and/or validate systems-level software, hardware, architecture, algorithms, and solutions that enables the development of cutting-edge technology. Qualcomm Systems Engineers collaborate across functional teams to meet and exceed system-level requirements and standards. Minimum Qualifications Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 8+ years of Systems Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Systems Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience. Principal Engineer – Machine Learning We are looking for a Principal AI/ML Engineer with expertise in model inference , optimization , debugging , and hardware acceleration . This role will focus on building efficient AI inference systems, debugging deep learning models, optimizing AI workloads for low latency, and accelerating deployment across diverse hardware platforms. In addition to hands-on engineering, this role involves cutting-edge research in efficient deep learning, model compression, quantization, and AI hardware-aware optimization techniques . You will explore and implement state-of-the-art AI acceleration methods while collaborating with researchers, industry experts, and open-source communities to push the boundaries of AI performance. This is an exciting opportunity for someone passionate about both applied AI development and AI research , with a strong focus on real-world deployment, model interpretability, and high-performance inference . Education & Experience 20+ years of experience in AI/ML development, with at least 5 years in model inference, optimization, debugging, and Python-based AI deployment. Master’s or Ph.D. in Computer Science, Machine Learning, AI Leadership & Collaboration Lead a team of AI engineers in Python-based AI inference development. Collaborate with ML researchers, software engineers, and DevOps teams to deploy optimized AI solutions. Define and enforce best practices for debugging and optimizing AI models Key Responsibilities Model Optimization & Quantization Optimize deep learning models using quantization (INT8, INT4, mixed precision etc), pruning, and knowledge distillation. Implement Post-Training Quantization (PTQ) and Quantization-Aware Training (QAT) for deployment. Familiarity with TensorRT, ONNX Runtime, OpenVINO, TVM AI Hardware Acceleration & Deployment Optimize AI workloads for Qualcomm Hexagon DSP, GPUs (CUDA, Tensor Cores), TPUs, NPUs, FPGAs, Habana Gaudi, Apple Neural Engine. Leverage Python APIs for hardware-specific acceleration, including cuDNN, XLA, MLIR. Benchmark models on AI hardware architectures and debug performance issues AI Research & Innovation Conduct state-of-the-art research on AI inference efficiency, model compression, low-bit precision, sparse computing, and algorithmic acceleration. Explore new deep learning architectures (Sparse Transformers, Mixture of Experts, Flash Attention) for better inference performance. Contribute to open-source AI projects and publish findings in top-tier ML conferences (NeurIPS, ICML, CVPR). Collaborate with hardware vendors and AI research teams to optimize deep learning models for next-gen AI accelerators. Details Of Expertise Experience optimizing LLMs, LVMs, LMMs for inference Experience with deep learning frameworks: TensorFlow, PyTorch, JAX, ONNX. Advanced skills in model quantization, pruning, and compression. Proficiency in CUDA programming and Python GPU acceleration using cuPy, Numba, and TensorRT. Hands-on experience with ML inference runtimes (TensorRT, TVM, ONNX Runtime, OpenVINO) Experience working with RunTimes Delegates (TFLite, ONNX, Qualcomm) Strong expertise in Python programming, writing optimized and scalable AI code. Experience with debugging AI models, including examining computation graphs using Netron Viewer, TensorBoard, and ONNX Runtime Debugger. Strong debugging skills using profiling tools (PyTorch Profiler, TensorFlow Profiler, cProfile, Nsight Systems, perf, Py-Spy). Expertise in cloud-based AI inference (AWS Inferentia, Azure ML, GCP AI Platform, Habana Gaudi). Knowledge of hardware-aware optimizations (oneDNN, XLA, cuDNN, ROCm, MLIR, SparseML). Contributions to open-source community Publications in International forums / conferences / journals Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers. 3072372 Show more Show less

Uber Eats is seeking a highly skilled and motivated Staff Data Scientist to join our Search Team. In this role, you will be a key driver in enhancing the search experience for millions of users across the globe. You'll bring deep statistical expertise to guide decision-making, improve product performance, and ensure our evaluations and insights are rooted in methodological rigor. What You'll Do Conduct robust statistical analyses on complex datasets to identify product opportunities, shape roadmap priorities, and optimize user experiences in search. Design and evaluate A/B tests and quasi-experiments, applying best practices in experimental methodology to ensure high-quality, unbiased insights. Build and maintain statistical frameworks for defining and measuring ground truth - identifying reliable signals to evaluate search relevance, personalization, and user satisfaction. Apply advanced sampling strategies to construct representative datasets for both offline and online evaluation pipelines, ensuring scalability and statistical power. Develop rigorous evaluation metrics that reflect real-world product performance and align closely with user and business goals. Lead initiatives to strengthen causal inference practices across the team, applying methods like matching, regression discontinuity, and difference-in-differences where appropriate. Partner with product managers, engineers, and other scientists to translate open-ended product questions into structured analytical approaches. Provide mentorship and technical leadership to other scientists, promoting a culture of statistical excellence and continuous learning. What You'll Need: M.S. or Bachelor's degree in Statistics, Economics, Mathematics, Operations Research, Computer Science, or a related quantitative field. 10+ years of industry experience in data science or applied analytics, ideally with experience in consumer products, search, or recommendation systems. Deep expertise in ground truth design, and evaluation methodologies for complex user-facing systems. Proven experience with statistical sampling techniques and working with offline evaluation pipelines to assess models and product performance. Strong fluency in experimentation design, causal inference, and observational data analysis. Proficiency with tools like SQL, Python, and R for data manipulation, modeling, and visualization. Excellent communication skills - able to present statistical findings clearly and influence product and engineering decisions through data. A strong product sense and the ability to balance analytical rigor with practical business impact. Show more Show less

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com Job Function Data Analytics & Computational Sciences Job Sub Function Biostatistics Job Category Scientific/Technology All Job Posting Locations: PENJERLA, Telangana, India Job Description Position Summary The Principal Statistician supports the design, execution, analysis, interpretation, and reporting or communication of data evidence for Pre/Early/Late Clinical Development, Research & Discovery, Medical Affairs, Real World Evidence, or Manufacturing Sciences programs for research, development, and/or marketed product needs in Janssen, with minimal supervision. This position supports statistical aspects of business-critical and/or regulatory commitments, provides input to program plans with limited supervision, and represents Statistics & Decision Sciences (SDS) for cross-functional and intra-departmental teams or working groups. He/She abides by the Credo and practices J&J Leadership Imperatives for Individuals: Lead, Shape, Connect, and Deliver. Position Core Competencies, Responsibilities And Accountabilities Expertise: Demonstrates advanced data analytic expertise based on a foundation of statistical principles and a strong track record of applied experience leading to successful program support. Is effective in the use of relevant computational tools for study, experiment, or trial research objectives. Applies high quality statistical methodology in assigned projects with demonstrated understanding of the disease/scientific/functional area and health authority acceptability. Quality and Compliance: Complies with organization and company standard operating procedures in timely fashion, such as training and project time accounting. Understands and aligns with relevant regulatory guidances. Contributes high quality and timely deliverables as assessed by stakeholders such as the project team, the clinical trial team, and the Statistics Area Head. Ensures that documents, specifications, programs, and macros are consistent and comply with project and company standards. Follows best practices for Data Integrity. Drug Development : Demonstrates thorough knowledge of pharmaceutical research and development strategies and execution. Takes a lead in providing SDS support to experimental design, modeling, analysis planning, analysis execution, interpretation, and statistical communications. Is accountable for execution of individual project responsibilities, including: meetings with necessary project team members, reporting activities, exploratory analyses/graphics, and additional analyses to support publications for individual clinical trials/studies/projects. Is an evolving leader for providing input to team in terms of optimizing study or trial designs in line with study or indication level objectives, and supports scenario simulations and sample size calculations based on relevant technical and disease/scientific/functional area knowledge. Disease Area Knowledge: Demonstrates knowledge for at least one disease area/target . Innovation: Suggests and performs the evaluation of alternative or innovative approaches to statistical methods or business processes. Representation: Represents Statistics & Decision Sciences for cross-functional and intra-departmental teams or working groups relating to scientific or process initiatives. External Engagement: Participates as a member of professional organizations, e.g. by attending meetings as chair or presenter. Mentor: Supervises contractors/special assignment personnel/interns/co-ops as required. Mentors junior colleagues in techniques, processes, and responsibilities. Process: Participates in process improvement or standards development initiatives. Complexity: Works on increasingly more complex programs after mastering standard ones. Proactively identifies complexity in terms Scientific, Statistical, Health Authority, Operational, and Partnership issues. Collaboration: Builds cross-functional partnerships with internal colleagues and with external partners (e.g. Contract Research Organizations (CROs), consultants) to achieve results for project specific needs with focus on improving communication, efficiency, and productivity. Works cross-functionally to identify and resolve issues. Communication: Has very good written, oral, and interpersonal communication skills. Demonstrated ability to collaborate and consult with non-statisticians, translating complex statistical concepts to drug research & development partners. Bridges scientific and business needs – integrating quantitative sciences and strong disease or functional area knowledge and appropriate market/competitive intelligence. Programming: Demonstrates full proficiency in SAS or R, as well as a working knowledge of other relevant computational tools as required. Area Specific Core Competencies, Responsibilities And Accountabilities These are additional to the above position core competencies, applicable to individuals according to their assigned area within Statistics & Decision Sciences. Discovery & Translational Documents projects in sufficient detail for reproducibility. Serves as initial consultation contact for new projects. Maintains and grows customer base, and builds loyal relationships with customers. Assumes independent, professional responsibility for all phases of a project request from beginning through completion, with minimal supervision as needed. Manages multiple projects. Leads Statistical Input for at least one functional area, research field, or compound. Provides input to product development and performs statistical functions for submission related activities where appropriate. Statistical Modeling & Methodology Support broad implementation of innovative statistical approaches across the development portfolio. Support development and implementation of innovative approaches, participating in their hands-on implementation through direct interactions with statisticians. This involves, but is not limited to, identifying appropriate designs and methods, decision rules (e.g., Go/No Go); planning, running, and summarizing simulation studies to evaluate the operating characteristics of alternative designs and methods under a range of scenarios; and participating in the implementation of the selected approaches by engaging in protocol and SAP write-up. Collaborate with external consultants to provide support in the development and implementation of innovative methods and designs. Identify opportunities for innovation; interact directly with statisticians and other QS scientists for early identification of opportunities for innovative approaches. Participate in training and presentations on innovative approaches across the R&D organization (including statisticians, pharmacometricians, clinicians, and other stakeholder groups) to ensure awareness and adequate knowledge about these methods. Keep up-to-date knowledge of designs and analysis methods for clinical trials, including adaptive designs, model-based methods, etc. May engage in external collaborations within professional associations (e.g., ASA, IBS, SCT, ISoP, ISCB, PSI, EFPSI), participating in working groups, program committees, organizing sessions and presenting at scientific meetings, and publishing in peer reviewed journals. Knowledge of biostatistics applied to clinical trials and model-based drug development. Some experience with planning, running, and documenting simulations (including, but not limited to clinical trial simulations). Awareness of Bayesian methods and inference. Manufacturing & Toxicology Documents projects in sufficient detail for reproducibility, including entry in project tracking systems and placement into shared repositories. Serves as initial consultation contact for new projects. Maintains and grows customer base, and builds loyal relationships with customers. Assumes independent, professional responsibility for all phases of a project request from beginning through completion, with minimal supervision as needed. Manages multiple projects. Leads Statistical Input for at least one functional area, research field, or compound. Provides input to product development and performs statistical functions for submission related activities where appropriate. Medical Affairs Provides critical statistical oversight to Medical Affairs clinical studies and assumes a leadership role in clinical trial and/or patient registries planning (mostly Phase 3b/4 trials or observational studies for post marketing commitments/requirements) and reporting related activities; assumes the role of a Statistics representative for cross-functional teams and works on several trials (projects) simultaneously. Provides statistical input for clinical trials, observational studies and other types of clinical research projects including but not limited to post-hoc analyses, investigator initiated studies, publications, and HECOR/Epidemiology/Market Access support; Contributes/leads clinical study design, analysis planning and for the development of statistical analysis plan (SAP) and data presentation plan (DPS) for MA studies; Provides input to product development and performs statistical functions for submission related activities; Provides statistical support to other disciplines related to clinical statistics (e.g., HECOR/Epidemiology and publication activities); May serve as a primary contact with outside investigators (and vendors)in the preparation of scientific presentations and manuscripts; may interact with external Key Opinion Leaders (KOLs) and pursues rigorous statistical analyses in support of business-critical new research ideas; Explores and implements innovative statistical methods; Represents department in meetings with regulatory agencies. Real World Evidence Proactively interface with clinical teams to identify opportunities where real-world data analysis can support the clinical development feasibility assessment; Serve as liaison between the TA Clinical Teams and the Epidemiology Analytics Team to facilitate the translation of protocol Inclusion/Exclusion criteria into meaningful data definitions, and to track and measure outcomes; Work with RWE Feasibility Lead to shape and influence the future of protocol development through the use of novel technology applied to real world data to enhance data-driven operational decision making; Work closely with key stakeholders, including the Study Placement & Analytics group and the Clinical Program Leader, to run RWE analysis that support protocol design and protocol feasibility. Supervision and Reporting Relationships This position reports to a Director or above, and is an individual contributor position. Interfaces Internal: Statistics & Decision Sciences, Clinical Pharmacology & Pharmacometrics, Clinical Teams (or Equivalent) and associated working groups, Statistical Programming, Medical Writing, Leaders and Scientists within Therapeutic and Functional Areas, R&D Operations, Medical Affairs, Manufacturing, Safety, Regulatory Affairs, Quality, Human Resources, Information Technology, Finance. External: Contracted Partners, Academia, Professional Societies, Private and Public Consortia. Education And Experience Requirements Ph.D. in Statistics or related field with minimum 3 years relevant experience, or Master’s in Statistics or related field with commensurate years of relevant experience. Proficient in SAS or R programming. Good written, oral, and interpersonal communication skills. Ability to work independently. Demonstrated ability to work in interdisciplinary contexts outside statistics. Show more Show less

Uber Eats is seeking a highly skilled and motivated Staff Data Scientist to join our Search Team. In this role, you will be a key driver in enhancing the search experience for millions of users across the globe. You'll bring deep statistical expertise to guide decision-making, improve product performance, and ensure our evaluations and insights are rooted in methodological rigor. What You'll Do Conduct robust statistical analyses on complex datasets to identify product opportunities, shape roadmap priorities, and optimize user experiences in search. Design and evaluate A/B tests and quasi-experiments, applying best practices in experimental methodology to ensure high-quality, unbiased insights. Build and maintain statistical frameworks for defining and measuring ground truth - identifying reliable signals to evaluate search relevance, personalization, and user satisfaction. Apply advanced sampling strategies to construct representative datasets for both offline and online evaluation pipelines, ensuring scalability and statistical power. Develop rigorous evaluation metrics that reflect real-world product performance and align closely with user and business goals. Lead initiatives to strengthen causal inference practices across the team, applying methods like matching, regression discontinuity, and difference-in-differences where appropriate. Partner with product managers, engineers, and other scientists to translate open-ended product questions into structured analytical approaches. Provide mentorship and technical leadership to other scientists, promoting a culture of statistical excellence and continuous learning. What You'll Need: M.S. or Bachelor's degree in Statistics, Economics, Mathematics, Operations Research, Computer Science, or a related quantitative field. 10+ years of industry experience in data science or applied analytics, ideally with experience in consumer products, search, or recommendation systems. Deep expertise in ground truth design, and evaluation methodologies for complex user-facing systems. Proven experience with statistical sampling techniques and working with offline evaluation pipelines to assess models and product performance. Strong fluency in experimentation design, causal inference, and observational data analysis. Proficiency with tools like SQL, Python, and R for data manipulation, modeling, and visualization. Excellent communication skills - able to present statistical findings clearly and influence product and engineering decisions through data. A strong product sense and the ability to balance analytical rigor with practical business impact. Show more Show less

Location: IN - Hyderabad Telangana Goodyear Talent Acquisition Representative: Maria Monica Fernando Canding Sponsorship Available: No Relocation Assistance Available: No Job Responsibilities You analyze business and technical needs, translating processes into practice using the current Information Technology toolsets. You implement new solutions through configuration and the creation of functional specifications, facilitating solution realization. You conduct full integration testing of new or changed business/technical processes, and develop business/technical cycle tests for use by stakeholders. You document all process changes and share relevant knowledge with stakeholders. You troubleshoot, investigate, and persist in finding solutions to problems with unknown causes, where precedents do not exist, by applying logic, inference, creativity, and initiative. You provide cross-functional support and maintenance for the responsible business/technical areas. You conduct cost/benefit analyses by evaluating alternative design approaches to determine the best-balanced solution. The best-balanced solution satisfies immediate stakeholder needs, meets system requirements, and facilitates subsequent change. You assume a leadership role in small initiatives, playing the key contributor, facilitator, or group lead. Qualifications You hold a Bachelor's degree in MIS, Computer Science, Engineering, Technology, Business Administration, or, in lieu of a degree, have 9 years of IT experience. You have at least 4 years of experience in IT, with a minimum of 2 years of experience in SAP. You possess techno-functional knowledge of SAP IT applications in the relevant business area. You have the ability to understand business processes and needs, delivering prompt, efficient, and high-quality service to the business. You have strong analytical and problem-solving skills, with excellent written and verbal communication skills and a strong command of English. You have solid solution design capabilities across functions and applications. You are able to work flexible hours as required for special occasions. Goodyear is an Equal Employment Opportunity and Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to that individual's race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender identity, age, physical or mental disability, ethnicity, citizenship, or any other characteristic protected by law. Goodyear is one of the world’s largest tire companies. It employs about 74,000 people and manufactures its products in 57 facilities in 23 countries around the world. Its two Innovation Centers in Akron, Ohio and Colmar-Berg, Luxembourg strive to develop state-of-the-art products and services that set the technology and performance standard for the industry. For more information about Goodyear and its products, go to www.goodyear.com/corporate Show more Show less

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Data Job Details About Salesforce We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place. We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place. We’re looking for an experienced Data Scientist who will help us build marketing attribution, causal inference, and uplift models to improve the effectiveness and efficiency of our marketing efforts. This person will also design experiments and help us drive consistent approach to experimentation and campaign measurement to support a range of marketing, customer engagement, and digital use cases. This Lead Data Scientist brings significant experience in designing, developing, and delivering statistical models and AI/ML algorithms for marketing and digital optimization use cases on large-scale data sets in a cloud environment. They show rigor in how they prototype, test, and evaluate algorithm performance both in the testing phase of algorithm development and in managing production algorithms. They demonstrate advanced knowledge of statistical and machine learning techniques along with ensuring the ethical use of data in the algorithm design process. At Salesforce, Trust is our number one value and we expect all applications of statistical and machine learning models to adhere to our values and policies to ensure we balance business needs with responsible uses of technology. Responsibilities As part of the Marketing Effectiveness Data Science team within the Salesforce Marketing Data Science organization, develop statistical and machine learning models to improve marketing effectiveness - e.g., marketing attribution models, causal inference models, uplift models, etc. Develop optimization and simulation algorithms to provide marketing investment and allocation recommendations to improve ROI by optimizing spend across marketing channels. Own the full lifecycle of model development from ideation and data exploration, algorithm design and testing, algorithm development and deployment, to algorithm monitoring and tuning in production. Design experiments to support marketing, customer experience, and digital campaigns and develop statistically sound models to measure impact. Collaborate with other data scientists to develop and operationalize consistent approaches to experimentation and campaign measurement. Be a master in cross-functional collaboration by developing deep relationships with key partners across the company and coordinating with working teams. Constantly learn, have a clear pulse on innovation across the enterprise SaaS, AdTech, paid media, data science, customer data, and analytics communities. Required Skills Master’s or Ph.D. in a quantitative field such as statistics, economics, industrial engineering and operations research, applied math, or other relevant quantitative field. 8+ years of experience designing models for marketing optimization such as multi-channel attribution models, customer lifetime value models, propensity models, uplift models, etc. using statistical and machine learning techniques. 8+ years of experience using advanced statistical techniques for experiment design (A/B and multi-cell testing) and causal inference methods for understanding business impact. Must have multiple, robust examples of using these techniques to measure effectiveness of marketing efforts and to solve business problems on large-scale data sets. 8+ years of experience with one or more programming languages such as Python, R, PySpark, Java. Expert-level knowledge of SQL with strong data exploration and manipulation skills. Experience using cloud platforms such as GCP and AWS for model development and operationalization is preferred. Must have superb quantitative reasoning and interpretation skills with strong ability to provide analysis-driven business insight and recommendations. Excellent written and verbal communication skills; ability to work well with peers and leaders across data science, marketing, and engineering organizations. Creative problem-solver who simplifies problems to their core elements. B2B customer data experience a big plus. Advanced Salesforce product knowledge is also a plus. Accommodations If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form. Posting Statement Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education. Show more Show less

Company Overview: Schneider Electric is a global leader in energy management and automation, committed to providing innovative solutions that ensure Life Is On everywhere, for everyone, and at every moment. We are part of small and medium buildings league, We are expanding our team in Gurugram and looking for a Principal Architect to enhance our Edge applications and drive the roadmap for next generations IOT gateways. Job Description: We are looking for an experienced Principal Architect - IoT Edge to lead the design and deployment of edge middleware for smart building environments. This role focuses on architecting robust, secure, and scalable IoT gateway-based systems that enable real-time monitoring, control, and optimization of micro-BMS, including HVAC, lighting, and energy. As a Principal Architect at Schneider Electric, you will play a crucial role in developing and implementing IoT solutions across our global infrastructure, with a primary focus on Edge software. This position requires a blend of strategic architectural design and practical hands-on ability to implement and manage, and optimize edge middleware solutions, ensuring efficient data processing for a large-scale edge gateways and devices (100s of thousands) deployed in the field. Some of the core services supported by IoT gateways aims at providing various services and features such as Secure firmware update Log management. Product configuration (identity, network connectivity, date/time…) Service/message bus (for intra and inter service communication) Controls logic to control and schedule downstream devices Device management, application management and connectivity to the “Cloud system” Edge intelligence – e.g. data buffering, computing metrics on edge Dockerised services Local Web Interface Connectivity protocols (MQTT, Zigbee, Wi-Fi, LoRaWAN, Modbus, BacNet …) Key Responsibilities: Provide architecture guidelines, identify technical solutions, and write technical requirements, answering to the functional requirement of the SMB BMS solution. Architect and develop scalable, high-performance Edge computing solutions for IoT applications. Work closely with POs and solution Architects of SMB- Building Activate platform to ensure proper landing of the middleware features and services Develop and optimize IoT data pipelines, integrating sensors, edge devices, and cloud-based platforms. Collaborate with cross-functional teams to define edge computing strategies, system architectures, and best practices. Work on device-to-cloud communication using MQTT(s), HTTP(s), WebSockets, or other messaging protocols. Ensure software is secure, reliable, and optimized for resource-constrained edge environments. Design and optimize Linux-based networking for edge devices, including network configuration, VPNs, firewalls, and traffic shaping. Implement and manage Linux process management, including systemd services, resource allocation, and performance tuning for IoT applications. Conduct code reviews, mentor junior developers, and provide technical leadership in edge software development. Implement edge analytics and AI/ML inference for predictive maintenance, energy optimization, and occupant comfort. Lead PoCs and pilot deployments in commercial, industrial, or mixed-use buildings. Requirements: Technical 10 – 12 years of overall experience in software engineering with a strong focus on IoT based firmware development Understanding of BACnet/Modbus protocols. Familiarity with cloud IoT platforms (AWS IoT, Azure IoT, Google Cloud IoT) and their integration with edge devices Strong knowledge of Linux networking, including TCP/IP, DNS, firewalls (iptables/nftables), VPNs, and network security. Experience in Linux process management, including systemd, resource limits (cgroups), and performance tuning. Good Understanding of IoT architectures, protocols (MQTT, HTTP/REST), and edge computing frameworks. Hands-on experience with Docker. Proficiency and Experience with Git or any other VCS. Excellent problem-solving skills and the ability to lead complex technical projects. Proficiency in edge programming (Python, GoLang, Rust, Java or C++) Knowledge of cybersecurity best practices for IOT environments. Good to have: Experience with digital twins, building energy modelling, or occupancy analytics. Expertise in Python, with experience in asynchronous programming, task processing frameworks, and Web frameworks Soft Skills: Excellent problem-solving abilities and strong communication skills. Advanced verbal and written communication skills including the ability to explain and present technical concepts to a diverse set of audiences. Comfortable working directly with both technical and non-technical audiences Good judgment, time management, and decision-making skills Strong teamwork and interpersonal skills; ability to communicate and thrive in a cross-functional environment Willingness to work outside documented job description. Has a “whatever is needed” attitude. Qualifications Preferred Qualifications: Bachelor's or Master's degree in computer science, Information Technology, or related field. Working experience on designing robust, scalable & maintainable IOT gateway applications Prior experience in building cloud connected Edge IoT solutions. Prior experience in the energy sector or industrial automation is advantageous. Primary Location : IN-Haryana-Gurgaon Schedule : Full-time Unposting Date : Ongoing

About The Role The Core Analytics & Science Team (CAS) is Uber's primary science organisation, covering both our main lines of business as well as the underlying platform technologies on which those businesses are built. We are a key part of Uber's cross-functional product development teams, helping to drive every stage of product development through data analytic, statistical, and algorithmic expertise. CAS owns the experience and algorithms powering Uber's global Mobility and Delivery products. We optimise and personalise the rider experience, target incentives and introduce customizations for routing and matching for products and use cases that go beyond the core Uber capabilities. What The Candidate Will Need / Bonus Points ---- What the Candidate Will Do ---- Refine ambiguous questions and generate new hypotheses and design ML based solutions that benefit product through a deep understanding of the data, our customers, and our business Deliver end-to-end solutions rather than algorithms, working closely with the engineers on the team to productionize, scale, and deploy models world-wide. Use statistical techniques to measure success, develop northstar metrics and KPIs to help provide a more rigorous data-driven approach in close partnership with Product and other subject areas such as engineering, operations and marketing Design experiments and interpret the results to draw detailed and impactful conclusions. Collaborate with data scientists and engineers to build and improve on the availability, integrity, accuracy, and reliability of data logging and data pipelines. Develop data-driven business insights and work with cross-functional partners to find opportunities and recommend prioritisation of product, growth, and optimisation initiatives. Present findings to senior leadership to drive business decisions ---- Basic Qualifications ---- Undergraduate and/or graduate degree in Math, Economics, Statistics, Engineering, Computer Science, or other quantitative fields. 6+ years experience as a Data Scientist, Machine learning engineer, or other types of data science-focused functions Knowledge of underlying mathematical foundations of machine learning, statistics, optimization, economics, and analytics Hands-on experience building and deployment ML models Ability to use a language like Python or R to work efficiently at scale with large data sets Significant experience in setting up and evaluation of complex experiments Experience with exploratory data analysis, statistical analysis and testing, and model development Knowledge in modern machine learning techniques applicable to marketplace, platforms Proficiency in technologies in one or more of the following: SQL, Spark, Hadoop ---- Preferred Qualifications ---- Advanced SQL expertise Proven track record to wrangle large datasets, extract insights from data, and summarise learnings/takeaways. Proven aptitude toward Data Storytelling and Root Cause Analysis using data Advanced understanding of statistics, causal inference, and machine learning Experience designing and analyzing large scale online experiments Ability to deliver on tight timelines and prioritise multiple tasks while maintaining quality and detail Ability to work in a self-guided manner Ability to mentor, coach and develop junior team members Superb communication and organisation skills Show more Show less

Senior Biostatistician Location: Bangalore, Homebased As a Senior Biostatistician you will be joining the world’s largest & most comprehensive clinical research organisation, powered by healthcare intelligence. What You Will Be Doing Supports design, analysis and interpretation, uses a wide range of statistical approaches and/or applicable software to explore options Authors analysis plans and prepares statistical inputs to key documents and presentation materials Contributes to the development of statistical strategy at a study-level, which may be shared with stakeholders Anticipates problems related to assigned work or areas of expertise and able to implement solutions, proactively seeking input from supervisor/manager You Are Having 5-8 years of experience in SAS and confidence in leading submission Having ability to perform Study Statistician role with minimal supervision Able to demonstrate strong statistical expertise with a good understanding of more complex design of experiments and inference methodologies (where applicable awareness / knowledge of Bayesian, Futility & Predictive Inference, Estimands, Missing Data etc.) Where required, have ability to actively participate in matrix team meetings What ICON Can Offer You Our success depends on the quality of our people. That’s why we’ve made it a priority to build a diverse culture that rewards high performance and nurtures talent. In addition to your competitive salary, ICON offers a range of additional benefits. Our benefits are designed to be competitive within each country and are focused on well-being and work life balance opportunities for you and your family. Our Benefits Examples Include Various annual leave entitlements A range of health insurance offerings to suit you and your family’s needs Competitive retirement planning offerings to maximise savings and plan with confidence for the years ahead Global Employee Assistance Programme, TELUS Health, offering 24-hour access to a global network of over 80,000 independent specialised professionals who are there to support you and your family’s well-being Life assurance Flexible country-specific optional benefits, including childcare vouchers, bike purchase schemes, discounted gym memberships, subsidised travel passes, health assessments, among others Visit our careers website to read more about the benefits of working at ICON: https://careers.iconplc.com/benefits At ICON, inclusion & belonging are fundamental to our culture and values. We’re dedicated to providing an inclusive and accessible environment for all candidates. ICON is committed to providing a workplace free of discrimination and harassment. All qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or in order to perform the essential functions of a position, please let us know through the form below. https://careers.iconplc.com/reasonable-accommodations Interested in the role, but unsure if you meet all of the requirements? We would encourage you to apply regardless – there’s every chance you’re exactly what we’re looking for here at ICON whether it is for this or other roles. Show more Show less

Research Scientist: Snapshot The Machine Learning and Optimization (MLO) team at Google DeepMind India is driven by the mission of enabling ultra-efficient, adaptable, and performant large models for everyone . Our mission is realized through foundational research in machine learning, specifically focusing on advancements in next-generation machine learning architectures, large-scale optimization algorithms, reinforcement learning methodologies, and innovative sampling techniques. We apply our research advances to critical product launches in Google, touching the lives of hundreds of millions of users, and we are looking forward to doing more! About Us Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority. In particular, our MLO team at GDM India, has deep expertise in machine learning fundamentals, large foundational models, reinforcement learning, generative modeling, and causal inference. Some of our breakthrough technologies include Matryoshka Representations and Matformers, Tandem Transformers, Treeformer, Causal Representation Learning . We have been at the forefront of reimagining Google’s latest foundational models from an efficiency and adaptability viewpoint, while also disseminating our findings through publications at top ML conferences/journals. The role Research Scientists at Google DeepMind lead our efforts in developing novel algorithmic architecture towards the end goal of solving and building Artificial General Intelligence. Having pioneered research in the world's leading academic and industrial labs in PhDs, post-docs or professorships, Research Scientists join Google DeepMind to work collaboratively within and across Research fields. They develop solutions to fundamental questions in machine learning and AI. Key Responsibilities Design, implement and evaluate models, agents and software prototypes of large foundational models. Deep dive into fundamentals of both the ML aspects of foundational models (like architectures, loss functions, data, evals) as well as their implementation on neural accelerators (efficiency during training, serving). Report and present research findings and developments including status and results clearly and efficiently both internally and externally, verbally and in writing. Suggest and engage in team collaborations to meet ambitious research goals. Work with external collaborators and maintain relationships with relevant research labs and key individuals as appropriate. Work in collaboration with our Responsible AI teams to ensure our advances in intelligence are developed ethically and provide broad benefits to humanity. About You In order to set you up for success as a Research Scientist at Google DeepMind India, we look for the following skills and experience: PhD in a technical field or equivalent practical experience. In addition, the following would be an advantage: PhD in Machine Learning, Computer Vision, Natural Language Processing or related areas A proven track record of publications and relevant experience in one or more areas such as large foundational models, ML+Systems, optimization, learning theory, computer vision, NLP etc. Proven experience with ML frameworks (e.g. JAX) and proven experience with training large models Proven experience working in industry, working on projects from proof-of-concept through to implementation, applying experimental ideas to applied problems A real passion for AI, Optimization, and Efficiency! Next steps Please fill out the required application form linked here and then continue on with the application on this page. Thank you! At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. Show more Show less

ob Title: AI Full stack Developer – GenAI & NLP Location: Pune, India (Hybrid) Work Mode: Remote Experience Required: 2+ Years (Relevant AI/ML with GenAI & NLP) Salary: Up to ₹15 LPA (CTC) Employment Type: Full-time Department: AI Research & Development Role Overview We are looking for a passionate AI Developer with strong hands-on experience in Generative AI and Natural Language Processing (NLP) to help build intelligent and scalable solutions. In this role, you will design and deploy advanced AI models for tasks such as language generation, summarization, chatbot development, document analysis, and more. You’ll work with cutting-edge LLMs (Large Language Models) and contribute to impactful AI initiatives. Key Responsibilities Design, fine-tune, and deploy NLP and GenAI models using LLMs like GPT, BERT, LLaMA, or similar. Build applications for tasks like text generation, question-answering, summarization, sentiment analysis, and semantic search. Integrate language models into production systems using RESTful APIs or cloud services. Evaluate and optimize models for accuracy, latency, and cost. Collaborate with product and engineering teams to implement intelligent user-facing features. Preprocess and annotate text data, create custom datasets, and manage model pipelines. Stay updated on the latest advancements in generative AI, transformer models, and NLP frameworks. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field. Minimum 2 years of experience in fullstack development and AI/ML development, with recent work in NLP or Generative AI. Hands-on experience with models such as GPT, T5, BERT, or similar transformer-based architectures. Proficient in Python and libraries such as Hugging Face Transformers, spaCy, NLTK, or OpenAI APIs. Hands-on experience in any frontend/ backend technologies for software development. Experience with deploying models using Flask, FastAPI, or similar frameworks. Strong understanding of NLP tasks, embeddings, vector databases (e.g., FAISS, Pinecone), and prompt engineering. Familiarity with MLOps tools and cloud platforms (AWS, Azure, or GCP). Preferred Qualifications Experience with LangChain, RAG (Retrieval-Augmented Generation), or custom LLM fine-tuning. Knowledge of model compression, quantization, or inference optimization. Exposure to ethical AI, model interpretability, and data privacy practices. What We Offer Competitive salary package up to ₹15 LPA. Remote work flexibility with hybrid team collaboration in Pune. Opportunity to work on real-world generative AI and NLP applications. Access to resources for continuous learning and certification support. Inclusive, fast-paced, and innovative work culture. Skills: r,kubernetes,next.js,docker,rag architectures,large language models (llms),gcp,embeddings,large language models,bert,javascript,django,machine learning (ml),cloud,tensorflow,machine learning,openai,artificial intelligence,natural language processing (nlp),vector databases,nltk,ai tools,langchain,fastapi,ml,typescript,react.js,java,deep learning,ai development,aws,flask,natural language processing,gpt,nlp tasks,hugging face,hugging face transformers,mlops tools,azure,generative ai,ai technologies,google cloud,node.js,python,nlp,spacy,mlops,ci/cd,pytorch,computer vision Show more Show less

Flexera saves customers billions of dollars in wasted technology spend. A pioneer in Hybrid ITAM and FinOps, Flexera provides award-winning, data-oriented SaaS solutions for technology value optimization (TVO), enabling IT, finance, procurement and cloud teams to gain deep insights into cost optimization, compliance and risks for each business service. Flexera One solutions are built on a set of definitive customer, supplier and industry data, powered by our Technology Intelligence Platform, that enables organizations to visualize their Enterprise Technology Blueprint™ in hybrid environments—from on-premises to SaaS to containers to cloud. We’re transforming the software industry. We’re Flexera. With more than 50,000 customers across the world, we’re achieving that goal. But we know we can’t do any of that without our team. Ready to help us re-imagine the industry during a time of substantial growth and ambitious plans? Come and see why we’re consistently recognized by Gartner, Forrester and IDC as a category leader in the marketplace. Learn more at flexera.com Job Summary: We are seeking a skilled and motivated Senior Data Engineer to join our Automation, AI/ML team. In this role, you will work on designing, building, and maintaining data pipelines and infrastructure to support AI/ML initiatives, while contributing to the automation of key processes. This position requires expertise in data engineering, cloud technologies, and database systems, with a strong emphasis on scalability, performance, and innovation. Key Responsibilities: Identify and automate manual processes to improve efficiency and reduce operational overhead. Design, develop, and optimize scalable data pipelines to integrate data from multiple sources, including Oracle and SQL Server databases. Collaborate with data scientists and AI/ML engineers to ensure efficient access to high-quality data for training and inference models. Implement automation solutions for data ingestion, processing, and integration using modern tools and frameworks. Monitor, troubleshoot, and enhance data workflows to ensure performance, reliability, and scalability. Apply advanced data transformation techniques, including ETL/ELT processes, to prepare data for AI/ML use cases. Develop solutions to optimize storage and compute costs while ensuring data security and compliance. Required Skills and Qualifications: Experience in identifying, streamlining, and automating repetitive or manual processes. Proven experience as a Data Engineer, working with large-scale database systems (e.g., Oracle, SQL Server) and cloud platforms (AWS, Azure, Google Cloud). Expertise in building and maintaining data pipelines using tools like Apache Airflow, Talend, or Azure Data Factory. Strong programming skills in Python, Scala, or Java for data processing and automation tasks. Experience with data warehousing technologies such as Snowflake, Redshift, or Azure Synapse. Proficiency in SQL for data extraction, transformation, and analysis. Familiarity with tools such as Databricks, MLflow, or H2O.ai for integrating data engineering with AI/ML workflows. Experience with DevOps practices and tools, such as Jenkins, GitLab CI/CD, Docker, and Kubernetes. Knowledge of AI/ML concepts and their integration into data workflows. Strong problem-solving skills and attention to detail. Preferred Qualifications: Knowledge of security best practices, including data encryption and access control. Familiarity with big data technologies like Hadoop, Spark, or Kafka. Exposure to Databricks for data engineering and advanced analytics workflows. Flexera is proud to be an equal opportunity employer. Qualified applicants will be considered for open roles regardless of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by local/national laws, policies and/or regulations. Flexera understands the value that results from employing a diverse, equitable, and inclusive workforce. We recognize that equity necessitates acknowledging past exclusion and that inclusion requires intentional effort. Our DEI (Diversity, Equity, and Inclusion) council is the driving force behind our commitment to championing policies and practices that foster a welcoming environment for all. We encourage candidates requiring accommodations to please let us know by emailing careers@flexera.com. Show more Show less

Job Description We are looking for an exceptional Data Scientist with deep expertise in speech technologies, advanced NLP, and LLM fine-tuning to join our cutting-edge AI research team. In this pivotal role, you will be responsible for building and optimizing state-of-the-art machine learning pipelines that drive intelligent audio and language-based products. Your work will directly contribute to the development of next-generation AI solutions that are privacy-focused, high-performance, and built for scale. Key Responsibilities Develop and deploy real-time ASR pipelines, leveraging models like Whisper, wav2vec2, or custom speech models. Design and implement robust intent detection and entity extraction systems, utilizing transcribed speech, keyword spotting, and semantic pattern recognition. Fine-tune LLMs and transformer architectures (BERT, RoBERTa, etc.) for tasks including intent classification, entity recognition, and contextual comprehension. Optimize end-to-end pipelines for mobile and on-device inference, employing tools like TFLite, ONNX, quantization, and pruning to achieve low-latency performance. Collaborate closely with AI product teams and MLOps engineers to ensure seamless deployment, continuous iteration, and performance monitoring. Required Technical Skills Hands-on experience with ASR models (Whisper, wav2vec2, DeepSpeech, Kaldi, Silero), with a focus on fine-tuning for Indian languages and multilingual scenarios. Strong command of NLP techniques such as keyword spotting, sequence labeling, masked token prediction, and rule-based classification. Proven track record in LLM and transformer fine-tuning for NER, intent detection, and domain-specific adaptation. Expertise in speech metadata extraction, feature engineering, and signal enrichment. Proficiency in model optimization methods like quantization-aware training (QAT), pruning, and efficient runtime deployment for edge devices. Excellent Python skills with proficiency in PyTorch or TensorFlow, along with solid experience in NumPy, pandas, and real-time data processing frameworks. Qualifications Bachelors or Masters degree in Computer Science, Electrical Engineering, Data Science, or a related technical field. Academic or industry background in speech processing, ASR, telecom analytics, or applied NLP is highly desirable. Portfolio showcasing real-world speech/NLP projects, open-source contributions, or published research will be a strong advantage. Experience 3 to 6+ years of applied experience in speech AI, NLP for intent detection, or machine learning model development. Proven success in building, deploying, and optimizing ML models for real-time, low-latency environments. Contributions to leading open-source projects like openai/whisper, mozilla/DeepSpeech, or facebook/wav2vec2 are highly valued. (ref:hirist.tech) Show more Show less

When you join Verizon You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife. What You’ll Be Doing... Join Verizon as we continue to grow our industry-leading network to improve the ways people, businesses, and things connect. We are looking for an experienced, talented and motivated AI&ML Engineer to lead AI Industrialization for Verizon. You will also serve as a subject matter expert regarding the latest industry knowledge to improve the Home Product and solutions and/or processes related to Machine Learning, Deep Learning, Responsible AI, Gen AI, Natural Language Processing, Computer Vision and other AI practices. Deploying machine learning models - On Prem, Cloud and Kubernetes environments Driving data-derived insights across the business domain by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives. Creating and implementing data and ML pipelines for model inference, both in real-time and in batches. Architecting, designing, and implementing large-scale AI/ML systems in a production environment. Monitor the performance of data pipelines and make improvements as necessary What We’re Looking For... You have strong analytical skills and are eager to work in a collaborative environment with global teams to drive ML applications in business problems, develop end-to-end analytical solutions, and communicate insights and findings to leadership. You work independently and are always willing to learn new technologies. You thrive in a dynamic environment and can interact with various partners and multi-functional teams to implement data science-driven business solutions. You'll Need To Have Bachelor's degree with four or more years of relevant work experience. Expertise in advanced analytics/ predictive modelling in a consulting role. Experience with all phases of end-to-end Analytics project Hands-on programming expertise in Python (with libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) , R (for specific data analysis tasks) Knowledge of Machine Learning Algorithms - Linear Regression , Logistic Regression ,Decision Trees ,Random Forests ,Support Vector Machines (SVMs) ,Neural Networks (Deep Learning) ,Bayesian Networks Data Engineering - Data Cleaning and Preprocessing ,Feature Engineering ,Data Transformation , Data Visualization Cloud Platforms - AWS SageMaker ,Azure Machine Learning ,Cloud AI Platform Even better if you have one or more of the following: Advanced degree in Computer Science, Data Science, Machine Learning, or a related field. Knowledge on Home domain with key areas like Smart Home, Digital security and wellbeing Experience with stream-processing systems: Spark-Streaming, Storm etc. #TPDNONCDIOREF Where you’ll be working In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager. Scheduled Weekly Hours 40 Equal Employment Opportunity Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics. Show more Show less

ob Title: AI Full stack Developer – GenAI & NLP Location: Pune, India (Hybrid) Work Mode: Remote Experience Required: 2+ Years (Relevant AI/ML with GenAI & NLP) Salary: Up to ₹15 LPA (CTC) Employment Type: Full-time Department: AI Research & Development Role Overview We are looking for a passionate AI Developer with strong hands-on experience in Generative AI and Natural Language Processing (NLP) to help build intelligent and scalable solutions. In this role, you will design and deploy advanced AI models for tasks such as language generation, summarization, chatbot development, document analysis, and more. You’ll work with cutting-edge LLMs (Large Language Models) and contribute to impactful AI initiatives. Key Responsibilities Design, fine-tune, and deploy NLP and GenAI models using LLMs like GPT, BERT, LLaMA, or similar. Build applications for tasks like text generation, question-answering, summarization, sentiment analysis, and semantic search. Integrate language models into production systems using RESTful APIs or cloud services. Evaluate and optimize models for accuracy, latency, and cost. Collaborate with product and engineering teams to implement intelligent user-facing features. Preprocess and annotate text data, create custom datasets, and manage model pipelines. Stay updated on the latest advancements in generative AI, transformer models, and NLP frameworks. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field. Minimum 2 years of experience in fullstack development and AI/ML development, with recent work in NLP or Generative AI. Hands-on experience with models such as GPT, T5, BERT, or similar transformer-based architectures. Proficient in Python and libraries such as Hugging Face Transformers, spaCy, NLTK, or OpenAI APIs. Hands-on experience in any frontend/ backend technologies for software development. Experience with deploying models using Flask, FastAPI, or similar frameworks. Strong understanding of NLP tasks, embeddings, vector databases (e.g., FAISS, Pinecone), and prompt engineering. Familiarity with MLOps tools and cloud platforms (AWS, Azure, or GCP). Preferred Qualifications Experience with LangChain, RAG (Retrieval-Augmented Generation), or custom LLM fine-tuning. Knowledge of model compression, quantization, or inference optimization. Exposure to ethical AI, model interpretability, and data privacy practices. What We Offer Competitive salary package up to ₹15 LPA. Remote work flexibility with hybrid team collaboration in Pune. Opportunity to work on real-world generative AI and NLP applications. Access to resources for continuous learning and certification support. Inclusive, fast-paced, and innovative work culture. Skills: computer vision,next.js,r,mlops,artificial intelligence,nltk,flask,aws,react.js,bert,hugging face,embeddings,google cloud,machine learning,machine learning (ml),natural language processing,hugging face transformers,natural language processing (nlp),ci/cd,nlp,django,python,large language models,pytorch,fastapi,large language models (llms),openai,ai technologies,typescript,ai tools,azure,kubernetes,gcp,llama,mlops tools,gpt,vector databases,javascript,rag architectures,nlp tasks,langchain,openai apis,spacy,docker,ai development,tensorflow,ml,node.js,generative ai,java,cloud,deep learning Show more Show less

Woxsen University is a premier institution at the forefront of technology and business education in India. Strategically located in Hyderabad's innovation corridor, we bridge academic excellence with industry relevance through cutting-edge programs and research initiatives. Our research-intensive faculty drive intellectual leadership that shapes academic discourse and advances the frontiers of computational sciences, artificial intelligence, and machine learning. Available Positions We are currently seeking research-focused professors specializing in the following disciplines: Computer Science & Engineering Artificial Intelligence Machine Learning Data Science Computational Systems Position Overview We seek accomplished research scholars with exceptional capabilities in investigating computational systems, algorithmic approaches, and intelligent technologies. The ideal candidates will demonstrate research excellence through publications in top-tier journals and conferences, and possess the ability to develop innovative research programs that advance the theoretical foundations and practical applications of computational sciences. These positions require individuals who can build significant research portfolios, mentor junior scholars, and lead interdisciplinary initiatives examining the mathematical, computational, and engineering dimensions of intelligent systems. Key Responsibilities Research & Scholarly Impact (70%) Maintain a rigorous research agenda resulting in publications in premier conferences and journals (NeurIPS, ICML, ICLR, CVPR, ICCV, ACL, AAAI, IJCAI, KDD, JMLR, TPAMI, TNNLS, etc.) Secure competitive research grants from national and international funding bodies (DST, SERB, MeitY, NSF, EU Horizon, industry research labs) Develop innovative algorithmic approaches, computational models, and system architectures Lead a research group focused on specific areas of computational sciences and AI/ML Design and implement cross-disciplinary research initiatives bridging computational approaches with domain applications Contribute to global research networks and collaborative projects with international scholars Apply the GTRMP framework with primary emphasis on research excellence and theoretical advancement Present research at prestigious academic conferences and research symposia Serve on program committees and editorial boards of leading conferences and journals Teaching & Student Development (20%) Teach advanced courses in computational sciences, AI/ML foundations, and specialized topics Supervise doctoral students and mentor early-career researchers in computational methods Develop research-informed curriculum for graduate programs in CS/AI/ML Create opportunities for student involvement in high-quality research projects Design specialized research seminars and workshops for doctoral students Foster interdisciplinary thinking and methodological rigor in student research Guide students in preparing submissions for top-tier conferences and journals Institutional Development & External Relations (10%) Contribute to departmental and university research governance Participate in faculty recruitment and development initiatives Support research accreditation and quality enhancement efforts Collaborate with colleagues on interdisciplinary computational research initiatives Enhance Woxsen's reputation as a center of excellence for computational sciences and AI research Develop relationships with external research institutions, industry research labs, and funding agencies Contribute to open-source software development and research infrastructure when appropriate Qualifications Essential PhD in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or related discipline from a globally recognized research institution Outstanding research profile with multiple publications in top-tier conferences and journals in computational sciences, AI, and ML Demonstrated success in securing competitive research grants Strong theoretical foundations and methodological expertise in computational and algorithmic approaches Evidence of research impact through citations, h-index, and scholarly recognition Experience in doctoral supervision and mentoring early-career researchers Excellent communication skills with ability to disseminate complex computational research to diverse audiences Active participation in international research networks and scholarly communities Desirable H-index of 20+ with a strong citation record Track record of publications at premier venues (NeurIPS, ICML, ICLR, CVPR, ACL, etc.) Experience leading funded research projects and managing research teams Contributions to open-source software, datasets, or research infrastructure Track record of successful research collaborations across institutions and disciplines Experience organizing workshops at major conferences or serving as area chair Demonstrated ability to bridge theoretical advances with computational implementations Experience with innovative methodological approaches and interdisciplinary applications Editorial or program committee experience with respected conferences and journals Record of successful PhD placement at research-intensive institutions Industry research experience at leading AI/ML labs (optional) Discipline-Specific Research Focus Areas Computer Science & Engineering Algorithm design and computational complexity High-performance computing and distributed systems Computer architecture and hardware-software co-design Programming languages and software engineering Security, privacy, and cryptographic systems Human-computer interaction and user experience Systems for AI/ML and computational infrastructure Artificial Intelligence Knowledge representation and reasoning Planning and decision-making under uncertainty Multi-agent systems and game-theoretic approaches AI for social good and ethical AI development Cognitive architectures and artificial general intelligence Human-AI collaboration and interactive AI systems Verification, validation, and safety of AI systems Machine Learning Deep learning architectures and optimization Reinforcement learning and sequential decision making Probabilistic models and Bayesian inference Unsupervised, self-supervised, and representation learning Transfer learning, meta-learning, and few-shot learning Fairness, accountability, transparency, and ethics in ML Theoretical foundations of machine learning Data Science Large-scale data processing and analytics Causal inference and experimental design Time series analysis and forecasting Network science and graph analytics Natural language processing and text mining Computer vision and multimedia analytics Scientific data analysis and computational statistics Computational Systems Embedded systems and IoT architectures Autonomous systems and robotics Cyber-physical systems and control theory Quantum computing and quantum information systems Computational biology and bioinformatics Computational sustainability and smart infrastructure Edge computing and mobile systems Show more Show less

IS Machine Learning Engineer At ABB, we are dedicated to addressing global challenges. Our core values: care, courage, curiosity, and collaboration - combined with a focus on diversity, inclusion, and equal opportunities - are key drivers in our aim to empower everyone to create sustainable solutions. Write the next chapter of your ABB story. This position reports to IS Global CX Analytics Manager Your role and responsibilities In this role, you will be responsible for the end-to-end development and deployment of AI-powered applications & includes designing and building AI interfaces, services, constructing AI-enabled infrastructure, and evaluating AI systems. Machine Learning Engineer will work collaboratively with cross-functional teams to incorporate AI capabilities into a wide range of products and services. The work model for the role is This role is contributing to the IS Services . You will be mainly accountable for: Running E2E development cycle of AI solutions based on the business requirements Following best software development practices to ensure high quality product and adherence to design objectives Evangelizing ABB and internal team on potential opportunities in AI Collaborate closely with data scientists, engineers, service owners to build products end-to-end on key initiatives Qualifications for the role Master's Degree or PhD in Computer Science, Computational or Applied Mathematics, or related areas with Artificial Intelligence specialty Strong communication skills with proficiency in English 5+ years of professional experience in AI/ML environments Track record of successful enterprise-level AI deployments: AI Application Development and Deployment/Scaling. Prompt engineering, Context construction. Nice to have: - - Inference optimization, Dataset engineering, Compute management, Data management Strong experience with AI infrastructure, including cloud platforms (Azure (must have), AWS/GCP optional) and containerization (Docker, Kubernetes), Azure AI Studio/Foundry/OpenAI, Hugging Face, .NET Framework, API Management & Azure infrastructure Strategic thinking and ability to translate business requirements into technical solutions Experience with SQL, MS Fabric, Databricks Experience in AI evaluation/responsible AI practices More about us Our mission in ABB IS (Information Systems) is to harness the power of information technology to deliver valuable, reliable, and competitive IS services for ABB. If you have a strong technical skills, analytical mind, and the drive to help us stay ahead of the competition, you are the one we are looking for. We value people from different backgrounds. Apply today for your next career step within ABB and visit www.abb.com to learn about the impact of our solutions across the globe. #MyABBStory Show more Show less

Key Responsibilities Work closely with clients to understand their business requirements and design data solutions that meet their needs. Develop and implement end-to-end data solutions that include data ingestion, data storage, data processing, and data visualization components. Design and implement data architectures that are scalable, secure, and compliant with industry standards. Work with data engineers, data analysts, and other stakeholders to ensure the successful delivery of data solutions. Participate in presales activities, including solution design, proposal creation, and client presentations. Act as a technical liaison between the client and our internal teams, providing technical guidance and expertise throughout the project lifecycle. Stay up-to-date with industry trends and emerging technologies related to data architecture and engineering. Develop and maintain relationships with clients to ensure their ongoing satisfaction and identify opportunities for additional business. Understands Entire End to End AI Life Cycle starting from Ingestion to Inferencing along with Operations. Exposure to Gen AI Emerging technologies. Exposure to Kubernetes Platform and hands on deploying and containorizing Applications. Good Knowledge on Data Governance, data warehousing and data modelling. Requirements Bachelor's or Master's degree in Computer Science, Data Science, or related field. 10+ years of experience as a Data Solution Architect, with a proven track record of designing and implementing end-to-end data solutions. Strong technical background in data architecture, data engineering, and data management. Extensive experience on working with any of the hadoop flavours preferably Data Fabric. Experience with presales activities such as solution design, proposal creation, and client presentations. Familiarity with cloud-based data platforms (e.g., AWS, Azure, Google Cloud) and related technologies such as data warehousing, data lakes, and data streaming. Experience with Kubernetes and Gen AI tools and tech stack. Excellent communication and interpersonal skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences. Strong problem-solving skills, with the ability to analyze complex data systems and identify areas for improvement. Strong project management skills, with the ability to manage multiple projects simultaneously and prioritize tasks effectively. Tools and Tech Stack Hadoop Ecosystem Data Architecture and Engineering: Preferred: Cloudera Data Platform (CDP) or Data Fabric. Tools: HDFS, Hive, Spark, HBase, Oozie. Data Warehousing Cloud-based: Azure Synapse, Amazon Redshift, Google Big Query, Snowflake, Azure Synapsis and Azure Data Bricks On-premises: , Teradata, Vertica Data Integration And ETL Tools Apache NiFi, Talend, Informatica, Azure Data Factory, Glue. Cloud Platforms Azure (preferred for its Data Services and Synapse integration), AWS, or GCP. Cloud-native Components Data Lakes: Azure Data Lake Storage, AWS S3, or Google Cloud Storage. Data Streaming: Apache Kafka, Azure Event Hubs, AWS Kinesis. HPE Platforms Data Fabric, AI Essentials or Unified Analytics, HPE MLDM and HPE MLDE AI And Gen AI Technologies AI Lifecycle Management: MLOps: MLflow, KubeFlow, Azure ML, or SageMaker, Ray Inference tools: TensorFlow Serving, K Serve, Seldon Generative AI Frameworks: Hugging Face Transformers, LangChain. Tools: OpenAI API (e.g., GPT-4) Kubernetes Orchestration and Deployment: Platforms: Azure Kubernetes Service (AKS)or Amazon EKS or Google Kubernetes Engine (GKE) or Open Source K8 Tools: Helm CI/CD For Data Pipelines And Applications Jenkins, GitHub Actions, GitLab CI, or Azure DevOps Show more Show less

Job Title: HPC Network Engineer Location: Mumbai Experience: Minimum 5 years of relevant network experience Job Overview: We are seeking a highly skilled and experienced HPC Network Engineer to join our team. The ideal candidate will have a strong background in setting up and managing high-performance computing (HPC) networks with cutting-edge technologies such as 400G and 800G network connectivity. This role involves designing, implementing, and troubleshooting complex network architectures tailored to HPC and GPU-based systems. The engineer will also play a critical role in enabling efficient GPU interconnects and scaling AI and HPC workloads. Key Responsibilities: HPC Network Deployment : Design, deploy, and maintain HPC networks with 400G/800G connectivity. Optimize network performance for large-scale computing environments. Advanced Networking Expertise : Deep understanding and hands-on experience with RoCE (RDMA over Converged Ethernet) and Infiniband technologies. Collaborate with cross-functional teams to architect and implement robust HPC networking solutions. Architectural Design and Communication : Develop and present complex network architectures to technical and non-technical stakeholders. Translate customer requirements into scalable and efficient network designs. GPU Communication Frameworks : Expertise in NVLink and NVSwitch for high-speed GPU-to-GPU communication. Optimize interconnects for distributed training and inference workloads. Technology Expertise : Hands-on experience with switches and networking equipment from Broadcom, Arista, Mellanox, Juniper, Cisco, SONiC, or Dell . Familiarity with NVIDIA, AMD, and Intel HPC architectures and their network integration requirements. Storage Networking for HPC and AI : Integrate GPUDirect Storage and NVMe-oF for efficient data movement between storage and GPUs. Optimize data pathways for high-speed storage access in HPC workloads. Problem Solving and Troubleshooting : Monitor, analyze, and troubleshoot network performance issues. Implement monitoring tools to ensure high availability and reliability of the HPC network. Customer-Centric Solutions : Engage with customers to understand their requirements and deliver tailored solutions on the fly. Provide ongoing support and documentation for implemented solutions. Comprehensive Network Knowledge : Expertise in end-to-end network monitoring, analysis, troubleshooting, and implementation. Stay updated on industry trends, standards, and best practices for HPC networking. AI and HPC Workload Integration : Support hybrid workloads combining AI and traditional HPC tasks. Scale large language models and scientific simulations across GPU clusters with minimal latency. Required Skills and Qualifications: Minimum 5 years of hands-on experience in core network engineering. Proven expertise in configuring and managing 400G or 800G network environments. Strong knowledge of RoCE and Infiniband protocols. Hands-on experience with NVLink and NVSwitch in GPU-based environments. Familiarity with networking equipment and technologies from vendors such as Broadcom, Arista, Mellanox, Juniper, Cisco, SONiC, or Dell . Experience working with NVIDIA, AMD, or Intel HPC and GPU architectures . Ability to conceptualize and explain complex network designs to diverse audiences. Strong analytical and troubleshooting skills in high-performance environments. Excellent communication and customer engagement skills to address requirements and provide solutions effectively. Preferred Qualifications: Industry certifications such as CCNP, CCIE, or equivalent. Experience in scripting and automation for network operations. Exposure to large-scale HPC deployments in data center environments. Knowledge of software-defined networking (SDN) and virtualized networking environments. Familiarity with AI-specific frameworks like TensorFlow , PyTorch , or Horovod in distributed setups. Why Join Us? Work on cutting-edge HPC and GPU-based technologies. Collaborate with industry leaders in AI and cloud infrastructure. Competitive compensation and growth opportunities. Opportunity to work in a dynamic and fast-paced environment. Show more Show less

Experience : 3.00 + years Salary : USD 30000-48000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: EOR Partner) (*Note: This is a requirement for one of Uplers' client - InsightNext) What do you need for this opportunity? Must have skills required: Algorithm, industry-specific AI, rapid prototyping, start-up, statistical modelling, AI systems, AI/ML, CI/CD, LLM, Ml frameworks, Cloud Server (Google / AWS), Python InsightNext is Looking for: Role Description This is a full-time remote role for a Senior AI/ML Engineer . The Senior AI/ML Engineer will spearhead the design, development, and deployment of advanced machine learning models, including Large Language Models (LLMs), Agentic AI Frameworks, and multimodal AI systems , tailored to diverse client needs across industries such as finance, healthcare, retail, and technology Responsibilities include client consultations, data preprocessing, model customization, performance optimization, and seamless integration of AI solutions into client ecosystems . The role requires staying ahead of AI/ML innovations, delivering high-impact consulting engagements, and producing comprehensive technical documentation to ensure client success. Key Responsibilities Collaborate with clients to assess business challenges and design bespoke AI solutions leveraging LLMs, agentic workflows, and multimodal models for applications like intelligent automation, predictive analytics, and natural language processing. Develop and fine-tune scalable AI/ML pipelines, utilizing distributed training, model compression, and low-latency inference to meet client-specific performance requirements. Perform advanced data preprocessing, handling diverse datasets (e.g., unstructured, multimodal, or streaming data) to ensure model robustness. Evaluate and benchmark model performance using metrics like BLEU, ROUGE, perplexity, or client-defined KPIs, ensuring alignment with business objectives. Stay at the forefront of AI/ML advancements (e.g., transformer architectures, neurosymbolic AI, retrieval augmented generation) to deliver cutting-edge solutions. Deploy AI models into client environments (e.g., cloud platforms, edge devices, or hybrid systems) using APIs and MLOps best practices. Provide thought leadership through client workshops, whitepapers, and presentations, showcasing expertise in AI trends and innovations. Mentor junior engineers and contribute to internal knowledge-sharing initiatives to elevate the firm’s AI consulting capabilities Qualifications- Technical Skills: Expertise in AI systems, ML frameworks, and Python Experience with cloud platforms (e.g. GCP, Azure and Azure) and development tools Strong programming skills in Python and modern software development practices such as CI/CD version controlling with Git Consulting Abilities: Client communication and solution presentation Strong project management track record Ability to thrive in fast-paced, remote, and cross-functional teams using agile methodologies Core Knowledge: Advanced knowledge of computer science, algorithms, and statistical modeling for probabilistic reasoning and uncertainty quantification People Skills: Excellent communication and teamwork abilities Education & Experience: Bachelors/Master's/Ph.D. in relevant field 3+ years AI/ML experience (2+ with clients) Proven industry solutions delivery Preferred Qualification: Industry-specific AI experience Rapid prototyping capabilities How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less