Location: Gurugram,Haryana,India   About US Material is a pioneering global partner in strategy, insights, design, and technology, driving customer centricity and digital relevance in a rapidly evolving, customer-led marketplace. Leveraging cutting-edge, science-based tools, Material offers unparalleled human understanding to forge transformative relationships between businesses and their customers. Through bespoke customer-centric business models, immersive experiences, and robust measurement systems, we empower businesses to thrive amidst ongoing digital transformation   Lead Data Scientist As the Lead Data Scientist, you will lead a team in developing AI solutions for metadata extraction, retrieval-augmented generation (RAG), and text-to-SQL models. Your role involves designing AI-driven solutions for schema retrieval, database integration, and model deployment in Azure. Responsibilities: Research, design, and develop ML models for metadata extraction, information retrieval, and RAG applications. Define AI architecture, tools, and Azure integrations, optimizing cloud-based model deployment. Implement schema retrieval pipelines using embeddings, FAISS/VectorDB, and ranking mechanisms. Develop pipelines for data preprocessing, metadata structuring, and structured query generation. Apply MLOps principles for scalable, automated AI/ML workflows. Enhance bot interactions with natural language processing, improving accuracy and reducing hallucinations. Deploy AI models and APIs on Azure, optimizing performance and cost. Perform testing for functional, integration, and load scenarios, ensuring query accuracy. Collaborate with cross-functional teams to define requirements and drive AI solutions. Must Have Skills: 6+ years in AI/ML, NLP, Python, with a strong focus on Azure. Expertise in RAG, NLP, Computer Vision, schema retrieval, and deep learning. Experience with FAISS/Vector DB, SQL, data preprocessing, and database integration in OneLake. Hands-on deployment and optimization of AI-powered bots and LLMs. Proficiency in microservices, Docker, and Kubernetes (Azure Kubernetes Service preferred). Strong MLOps practices, including CI/CD, monitoring, and lifecycle automation. Ability to optimize AI models for performance and efficiency in production. Strong Python skills with TensorFlow, PyTorch, LangChain, and FAISS. Excellent communication skills for technical and non-technical audiences. Apply to this job