Sr Data Scientist

Responsibilities

• End-to-End Development: Design, build, and productionize large-scale machine learning, generative AI and agentic systems and models.
• Operational Excellence: Implement robust MLOps workflows using MLflow to ensure model reliability, scalability, and performance tracking.
• Production Deployment: Take ownership of the full lifecycle of AI products, ensuring models move successfully from experimental stages to live production environments.
• Experience: 4+ years of hands-on experience in Data Science, Machine Learning, GenAI, and MLOps.
• Track Record: Proven experience productionizing models (must have moved models beyond the sandbox/prototype phase).

Technical Stack

• Required: Expert-level proficiency with MLflow and model deployment and monitoring on Databricks.
• Required: Experience with Databricks Spark, Lakebase, Vector Search.
• Required: Experience with at least one agent development framework like Langchain, Langgraph, DSPy etc.
• Good to have: Hands on experience with Databricks Apps, AI/BI Dashboards, Genie etc.
• Good to have: Databricks Asset Bundle (DAB), Git, experience with large repo management (GitHub, ADO etc.)

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