Data Scientist (AI/ML) Role

Key Responsibilities\n\n- Design and implement GenAI and Agentic AI solutions using Databricks Genie, Databricks Agent Bricks, Mosaic AI (model training, evaluation, prompt engineering, RAG)\n- Experience Build LLM-powered use cases\n- Design and build scalable data pipelines using Databricks, PySpark, and SQL\n- Implement Delta Lake, Unity Catalog, and medallion architecture\n- Optimize Spark jobs for performance, cost, and scalability\n- Perform data ingestion, transformation, and enrichment from multiple sources\n- Ensure data quality, reliability, and observability across pipelines\n- Support AI/ML workloads by preparing high‑quality, feature‑ready datasets\n- Develop and fine-tune LLMs/ML models using Databricks ML flow and Mosaic AI\n- Implement prompt engineering, model evaluation, and guardrails for enterprise GenAI use cases\n- Integrate AI solutions with enterprise data and business workflows