Lead Machine Learning Ops Engineer
Tasks
- Build CI/CD pipelines for ML
- Build and mature MLOps platform on Azure
- Coach team on MLOps best practices
- Collaborate on security and infrastructure standards
- Define MLOps vision and standards
- Define production ready ML requirements
- Deploy and serve production ML models
- Design ML packaging testing and documentation
- Design model handover process for operations
- Drive automated retraining and rollback procedures
- Evaluate MLOps tools and frameworks
- Implement model monitoring and observability
- Own end-to-end ML lifecycle
Perks/Benefits
- Brand discounts
- Commuter travel discounts
- Convenient commute with public transit
- Discounted travel opportunities
- Gym with classes
- Health and wellness benefits
- Outdoor activity access
- Restaurant and cafe access
- Transportation discounts and airport discounts
Skills/Tech-stack
Automated retraining | Azure | Azure Data | Azure Data Factory | Azure Databricks | Azure Machine Learning | CI/CD | Container Orchestration | Data Factory | Deployment Automation | Docker | Drift Detection | Experiment tracking | Feature management | Infrastructure as Code | Kubernetes | MLOps | MLflow | Machine Learning | Model Monitoring | Model Registry | Observability | Python | Terraform | “as-code”
Education
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