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About the role
Senior Data Scientist Join our high-performing team, honored with the prestigious Outstanding Data Engineering Team Award at DES 2025 for setting new benchmarks in data excellence. About the Role: We are looking for a skilled and passionate Data Scientist who brings hands-on expertise in Python programming, and Generative AI (GenAI) to help us design, build, and scale intelligent, AI-powered solutions. The ideal candidate will have deep experience with NLP, Computer Vision (CV), LLMs, FastAPI, vector databases, and modern machine learning pipelines. Key Responsibilities: • Design and implement AI/ML models for solving real-world business problems using Python and Azure ML. • Develop and deploy RAG-based solutions integrating embedding techniques, chunking, and retrieval strategies. • Work on OpenAI/GenAI-based models and fine-tune for specific enterprise use cases. • Build and consume REST APIs using FastAPI or Django. • Leverage Azure Form Recognizer for intelligent document processing. • Implement CI/CD pipelines for model deployment and automation. • Work with NoSQL and Vector Databases to store and retrieve high-dimensional data. • Collaborate with cross-functional teams to build scalable and robust ML pipelines. • Apply Deep Learning and NLP/CV techniques to enhance product features. Primary Skills Required: • Strong expertise in Python programming • Experience with GCP Cloud services. • Hands-on with FastAPI, framework • Good understanding of CI/CD pipelines • Proficiency in GenAI and OpenAI models • Expertise in NLP, Computer Vision, Machine Learning, and Deep Learning • Familiarity with NoSQL Databases (e.g., MongoDB, Cosmos DB) • Experience with Vector Databases (e.g., FAISS, Pinecone, Qdrant) • Knowledge of embedding & chunking techniques • Experience in building RAG (Retrieval-Augmented Generation) based solutions • Strong grasp of retrieval methods and information retrieval Notice Period - Immediate - 30 Days Location: Chennai, Coimbatore, Pune, Bangalore Experience : 6 Years -12 Years Regards, TA Team
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