Machine Learning Engineer 10027

Machine Learning Engineer

Centurion, Gauteng R - R Y AO Connect Solutions

Posted today

Job Description

Purpose of the Role

The Machine Learning Engineer is responsible for deploying, monitoring, and maintaining ML models in production. They turn prototype models into scalable, production-grade systems by building automated pipelines, integrating with infrastructure, and ensuring data and model quality. They work closely with Data Scientists, Data Engineers, and MLOps Support to ensure models are reliable, performant, and aligned with business objectives.

Responsibilities

• Translate models from notebooks to reusable, production-grade code.
• Build CI / CD pipelines for ML (unit tests, integration tests, automated deployment).
• Manage versioning of code, data, and models (e.g., Git, DVC).
• Monitor live models for drift, latency, and failure.
• Tune models and pipelines for performance and cost-efficiency.
• Implement load testing and alerting (Prometheus, Grafana, Azure Monitor).
• Collaborate with Data Engineers to manage feature pipelines and real-time data flow.
• Ensure training / inference data meets governance and compliance requirements.
• Implement Feature Store solutions where relevant (e.g., Azure Feature Store).
• Provide clear documentation for handover to MLOps support.
• Define IAM roles and controls for model access across dev / test / prod.
• Lead training or walkthroughs for deployment best practices.
• Introduce modern techniques like streaming inference, canary deployments, or serverless ML.
• Participate in post-mortems and incident reviews to strengthen MLOps maturity.

Required Skills & Experience

Education

Experience

Intermediate

Senior

Technical Skills

Competency Expectations

Performance Metrics

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