Data Scientist, ML Engineering

About the role

Senior ML engineering role focused on the platform that takes models to production at enterprise scale.

Responsibilities

• Architect end-to-end ML infrastructure: pipelines, serving, monitoring and governance.
• Deploy high-impact models (forecasting, optimization, NLP) with CI/CD on Azure Pipelines, MLflow and Databricks.
• Implement model registry, lineage, and drift monitoring with automated retraining.
• Mentor MLOps engineers.

Requirements

• 5–8+ years in ML engineering or MLOps.
• Strong Spark, Azure Databricks, MLflow, Kubernetes and Docker.