Description

You will own the operationalization and end-to-end management of machine learning models.

This role is hybrid.

Responsibilities

• Deploy ML models into production environments.
• Automate training, testing, and monitoring pipelines.
• Ensure model versioning and governance.
• Collaborate with data scientists to improve model performance.

Required Skills

• 3–7 years of experience in ML engineering.
• Strong proficiency in Python.
• Experience with CI/CD practices.
• Containerization using Docker and Kubernetes.
• Familiarity with Cloud MLOps platforms such as Azure ML, Kubeflow, or MLflow.
• Experience monitoring model drift and managing retraining cycles.

Key Skills

Education

Any Graduate