Senior MLOps Engineer
London, England, United Kingdom
R
A GBP 72K-95K (estimate) Senior-level Contract Full Time
Tasks
- Apply FinOps for cost visibility and right sizing
- Build and operate machine learning platforms on Azure
- Configure autoscaling traffic management rollback governance
- Deploy and manage ML workloads in Kubernetes
- Design end to end MLOps solutions
- Develop CI CD and continuous training pipelines
- Implement model serving for high availability and low latency
- Implement monitoring and observability for model and platform metrics
- Improve platform performance reliability throughput latency
- Manage containerized ML applications with Docker Kubernetes Helm GitOps
- Optimize cloud infrastructure utilization and spend
Perks/Benefits
- N/A
Skills/Tech-stack
Application Insights | Autoscaling | Azure | Azure DevOps | Azure Kubernetes | Azure Kubernetes Service | Azure Machine Learning | Azure Monitor | Bicep | CI/CD | Continuous Training | Docker | Drift Detection | FinOps | GitHub Actions | GitOps | Helm | Infrastructure as Code | Kubernetes | Kubernetes Service | Low Latency | Machine Learning | Microsoft Azure | Microsoft Azure Machine Learning | Model Drift | Model Drift Detection | Model Serving | Monitoring | Observability | Python | Terraform | Traffic Management | “as-code”
Education
N/A
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