Job descriptionDevelop and deploy end-to-end Machine Learning models using Python, Classical ML algorithms, and scalable Databricks workflows (PySpark, MLflow, Delta Lake).Lead GenAI initiatives including LLM fine-tuning, RAG pipelines, prompt engineering, and vector database integrations.Build robust data pipelines, perform feature engineering, and optimize models for performance and production readiness.Collaborate with cross-functional teams to translate business problems into ML / GenAI solutions with measurable outcomes.Conduct advanced statistical analysis, experimental design, and model evaluation to ensure accuracy and reliability.Drive best practices in MLOps, automation, and documentation for efficient model lifecycle management.