Principal Machine Learning Engineer
GBR-London-5 Canada Square, United Kingdom
GBP 80K-109K (estimate) Senior-level Full Time
Tasks
- Architect A B testing shadow and canary deployments
- Architect automated training deployment and retraining pipelines
- Create model cards and lineage artifacts
- Define end to end ML architecture
- Define model calibration and scoring logic
- Design low-latency inference services
- Design ranking scoring and similarity models
- Design scalable feature pipelines
- Enforce ML security and governance standards
- Establish data quality guardrails
- Generate regulator ready reason codes
- Implement explainability standards
- Implement infrastructure as code and ML CI CD
- Lead MLOps adoption
- Lead drift detection and observability
- Lead validation with golden datasets and benchmarks
- Manage model registry workflows
- Own telemetry and monitoring for models
- Secure cross account IAM patterns
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS SageMaker | Airtight Compliance Governance | B testing | Benchmarking | CI/CD | Canary Deployment | Compliance governance | Cross Account | Cross-account IAM | Data Quality | Data quality monitoring | Drift Detection | Encryption | Explainability | Feature Drift | Feature Drift Detection | Feature Engineering | Feature Store | Golden Dataset | IAM | Infrastructure as Code | Lineage | Low Latency | Low Latency Inference | MLOps | Model Cards | Model Governance | Model Monitoring | Model Registry | Model Serving | Observability | PII | PyTorch | Python | Quality monitoring | Real Time | Real-time Model Serving | SHAP | Shadow Deployment | Telemetry | TensorFlow | XGBoost | “as-code”
Education
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