MLOps Engineer Internship

Outcomes

• Build ML pipelines
• Deploy scalable ML systems
• Monitor drift and failures
• Manage feature stores
• Automate retraining workflows

Internship roadmap

1. 1
   ML Pipelines
2. 2
   Feature Stores
3. 3
   Model Serving
4. 4
   Drift + Monitoring
5. 5
   Production ML Systems

Curriculum timeline

• Week 1 — ML Pipelines

  Pipeline orchestration and reproducibility.
  2 tasks
• Week 2 — Feature Stores

  Feature engineering and online/offline serving.
  0 tasks

Task previews

Starter resources

• MLflow Docsdoc
• Kubeflow Docsdoc

FAQ