Senior MLOps Engineer
Tasks
- Build and maintain ML infrastructure
- Build monitoring and observability tools
- Build reinforcement learning orchestration pipelines
- Collaborate to deploy production grade models
- Create automated training validation and retraining pipelines
- Deploy and monitor production ML models
- Design end-to-end ML pipelines
- Develop model calibration and versioning
- Implement CI/CD pipelines for ML workflows
- Implement drift detection for data and model performance
Perks/Benefits
Skills/Tech-stack
Airflow | Apache Spark | CI/CD | Contextual Bandits | Databricks | Drift Detection | Feature Store | Git | GitHub Actions | GitLab | Kubeflow | MLflow | Machine Learning | Model calibration | Model versioning | Python | Q-learning | Reinforcement Learning | SQL | Unity Catalog
Education
N/A
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