MLOps Engineer - Databricks

Key Responsibilities

• Configure and optimise Databricks-based ML development and deployment frameworks.
• Implement model training, deployment, monitoring, and governance capabilities.
• Adapt or develop frameworks required to support migrated workloads.
• Build CI/CD pipelines and automation for ML life cycle management.
• Lead technical implementation of pilot models on the Global AI Platform.
• Develop reusable migration accelerators and standards.

Key Experience

• Databricks Lakehouse Platform.
• Databricks ML, MLflow, Unity Catalog, Workflows, and Model Serving.
• CI/CD and MLOps automation.
• Python and production ML deployment patterns.