Machine Learning Engineer

Key Responsibilities:

ML Platform & Pipelines:

• • Design and implement end-to-end ML pipelines for training, validation, packaging, and deployment.
• • Create reusable templates and tooling for experimentation, feature consumption, and model lifecycle management.

CI/CD & Release Engineering:

• • Build CI/CD for ML (tests, quality gates, approvals) using Azure DevOps/GitHub Actions.
• • Manage model registry, artifact versioning, and environment reproducibility.

Deployment, Monitoring & Reliability:

• • Implement batch and real-time serving patterns; automate monitoring for drift, performance, and data quality.
• • Establish SLOs/SLAs for ML services; lead incident response and root-cause analysis for ML production issues.

Cloud & Security:

• • Operate ML infrastructure...