Data Scientist (AI/ML) Role

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