Design, build, and productionize large-scale machine learning, generative AI, and agentic systems. Own the complete AI product lifecycle from experimentation through production deployment, implementing MLOps workflows with MLflow and Databricks to ensure reliability, scalability, monitoring, and performance. The role requires proven model productionization experience and expertise in Databricks technologies, agent development frameworks, and software repository management.
The ideal candidate possesses deep technical expertise in MLOps and GenAI.
Work Location: Hyderabad, Bangalore, Mumbai, Delhi, Gurgaon.
Work Mode: Work From Office 5 days a week
- 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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