Senior ML Ops Engineer
Holborn - London, United Kingdom
GBP 70K-102K (estimate) Senior-level Full Time
Tasks
- Communicate ML system health and risks
- Create feature engineering pipelines
- Create runbooks and documentation
- Define ML operational KPIs
- Deploy ML models to production
- Design automated ML pipelines
- Enforce model packaging and environment standards
- Establish MLOps governance and audit trails
- Implement ML specific CI CD pipelines
- Implement batch streaming and real time inference
- Implement drift detection and retraining triggers
- Maintain model registries
- Manage model rollback and rollout strategies
- Mentor junior engineers
- Operate ML monitoring and alerting
- Partner with Data Science for production readiness
- Set up experiment tracking
- Support data pipeline governance and quality controls
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Airflow | Alerting | Amazon SageMaker | Automation | Blue-Green Deployment | Blue/green | CI/CD | Canary Deployment | Data Quality | Docker | Drift Detection | ECS | EKS | Experiment tracking | Feast | Feature Store | Infrastructure as Code | Integration Testing | Kubernetes | Lambda | MLOps | MLflow | Machine Learning | Model Monitoring | Model Registry | Model Rollback | Model versioning | Observability | Prefect | Python | Step Functions | Tecton | TensorFlow Serving | Terraform | Testing Automation | Torchserve | Unit Testing | Weights and Biases | “as-code”
Education
N/A
Roles
Engineer | MLOps Engineer | Senior MLOps | Senior MLOps Engineer
Regions
Countries
States
Cities
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