Senior Data Scientist

Job Description :

We are looking for 6+ years of hands-on experience in Data Science, Machine Learning, GenAI, and MLOps in Hyderabad, Bangalore, Navi Mumbai, Delhi, Gurgaon.

Must have verifiable experience moving AI/ML models beyond the prototype/sandbox phase into live enterprise systems and also expertise in Databricks (proficiency with MLflow alongside model deployment and monitoring workflows on Databricks).

Solid experience utilizing Databricks Spark, Lakehouse/Lakebase concepts, and Vector Search.

Required Skills :

- Experience : 6+ years of hands-on experience in Data Science, Machine Learning, Gen AI, and MLOps.

The ideal candidate possesses deep technical expertise in MLOps and GenAI.

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 Ml flow 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 : 5+ years of hands-on experience in Data Science, Machine Learning, Gen AI, and MLOps.

Track Record :

- Proven experience in 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.

Experience : 5+ years of hands-on experience in Data Science, Machine Learning, Gen AI, and MLOps.

Track Record :

- Proven experience productionizing models (must have moved models beyond the sandbox/prototype phase).

Role & Responsibilities :

- Design, build, and productionize large-scale machine learning, generative AI and agentic systems and models.

- Implement robust MLOps workflows using Ml flow to ensure model reliability, scalability, and performance tracking.

- Take ownership of the full lifecycle of AI products, ensuring models move successfully from experimental stages to live production environments.