Description

You will build and deploy machine learning systems and internal enablement platforms in a regulated enterprise environment.

This role is on-site.

Responsibilities

• Design and implement ML models for classification and anomaly detection.
• Build and maintain APIs using Python and FastAPI.
• Deploy services using Docker and manage CI/CD pipelines in Azure.
• Develop internal platforms and shared services for product enablement.
• Ensure Responsible AI governance and data privacy compliance.

Required Skills

• 5+ years of experience in AI/ML engineering or applied data science.
• Strong proficiency in Python and SQL.
• Hands-on experience with ML/LLMOps tools (model registries, experiment tracking, prompt/version management).
• Experience building and deploying APIs/services (FastAPI or similar).
• Familiarity with containerization (Docker) and CI/CD.
• Experience working in cloud environments (Azure).
• Knowledge of Responsible AI, governance, and enterprise data privacy practices.

Preferred Skills

• Exposure to M365 Copilot extensibility or enterprise productivity tooling.
• Experience in regulated industries (insurance, auto warranty, financial services).

Key Skills

Education

Any Graduate