Machine Learning Engineer

Key Responsibilities:

ML Platform & Pipelines:

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

CI/CD & Release Engineering:

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

Deployment, Monitoring & Reliability:

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

Cloud & Security:

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  - Operate ML infr...