Senior MLOps Engineer

Senior MLOps Engineer — Databricks

Location: Noida / Gurugram · Hybrid
Experience Required: 6+ years overall (including 3+ in production with Databricks)
Notice Period: Immediate or within 30 days preferred

About the Role

You will own and operate our ML platform layer, ensuring that models move reliably from a data scientist's laptop to robust enterprise production. Using Databricks as your core stack, you will manage pipelines, model lifecycle, serving infrastructure, monitoring, and cost optimization.

Your Responsibilities:

• Build and operate production ML pipelines on Databricks (ingestion through retraining).
• Deploy using Databricks Asset Bundles and CI/CD for reliable releases across environments.
• Manage experiment tracking, model registration, versioning, and lineage via MLflow and Unity Catalog.
• Operate Model Serving endpoints with monitoring for latency, reliability, cost, drift, and data quality.
• Implement governance through Unity Catalog permissions and cluster policies.
• Tune Spark jobs to improve performance and reduce spend (Spark UI analysis).
• Troubleshoot production incidents and build recovery runbooks.

What You Bring:

• 6+ years of engineering experience with 3+ in Databricks production environments.
• Deep expertise in Unity Catalog, Delta Lake (MERGE, OPTIMIZE, Z-ordering), and schema evolution.
• Strong PySpark tuning skills to identify bottlenecks.
• End-to-end experience with MLflow deployments on Model Serving endpoints.
• Familiarity with Databricks Workflows, Auto Loader, DLT, or Lakeflow.
• Proficiency in Python/SQL, Git, CI/CD, and Docker.
• Solid fundamentals in feature engineering, evaluation, and model lifecycle management.