Sr Data Scientist - AI ML

Area(s) of responsibility 8 to 10 Years 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 highquality, featureready 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 Area(s) of responsibility 8 to 10 Years 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 highquality, featureready 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