Engineer - MLOps & Scientific Platforms - Data Foundry
US: South San Francisco, United States
USD 66K-165K Mid-level Full Time
Tasks
- Automate validation and deployments
- Build ML deployment pipelines
- Build dashboards and performance metrics
- Create API contracts and documentation
- Create model registry and feature pipelines
- Deploy predictive and analytical models
- Develop CI/CD pipelines for ML models
- Ensure API performance and reliability
- Expose tools via REST APIs
- Implement model versioning
- Implement structured logging and tracing
- Integrate model serving with data pipelines
- Operate model serving infrastructure
- Provide uncertainty quantification metrics
- Set up monitoring and alerting for data and ML systems
Perks/Benefits
- N/A
Skills/Tech-stack
API Testing | AWS | Azure | CI/CD | Cloud platform | Containerization | DVC | Distributed tracing | Docker | Drift Detection | Experiment tracking | Feature Engineering | Feature Stores | GRPC | Google Cloud | Google Cloud Platform | Infrastructure as Code | Kubernetes | MLOps | MLflow | Machine Learning | Model Monitoring | Observability | Python | REST APIs | Structured Logging | Weights and Biases | “as-code”
Education
Regions
Countries
States
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