ML Ops Engineer
Vauxhall, London
GBP 60K-80K (estimate) Mid-level Full Time Found 5d ago
Tasks
- Build automated retraining workflows
- Build production performance monitoring systems
- Champion ML engineering best practices
- Collaborate with data and ML engineers
- Conduct safe model rollouts
- Deploy ML models on AWS and edge devices
- Design scalable pipeline architectures
- Develop internal tooling for ML deployment
- Document processes and architecture
- Ensure compliance with healthcare security standards
- Establish data and feature management practices
- Implement infrastructure as code solutions
- Implement pipeline monitoring and alerting
- Improve experiment tracking infrastructure
- Maintain audit trails for models and data
- Manage ML pipelines with Airflow
- Manage model versioning with MLflow
- Optimize AWS resources and cost
- Participate in system architecture discussions
- Support Snowflake integrations
Perks/Benefits
Skills/Tech-stack
AWS | Alerting | Apache Airflow | Batch | CI/CD | CloudWatch | DVC | Data Versioning | Distributed Compute | Docker | EC2 | Git | HIPAA | Healthcare Security | IAM | Incident Response | Infrastructure as Code | Logging | MLflow | Model Serving | Model Serving Frameworks | Monitoring | Operational reliability | PHI handling | Python | Reproducibility | S3 | SOC 2 | Serving frameworks | Snowflake | Streaming Technologies | TensorFlow Serving | Torchserve | “as-code”
Education
Roles
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