Overview

Senior Machine Learning Operations Engineer London (2x a week onsite) - £500 p/d (Outside IR35) 6-months Contract

Responsibilities

• Evolve and scale the machine learning platform to support high-throughput model inference and fast iteration cycles.
• You will work closely with ML engineers and product teams to align infrastructure with evolving project needs, research and implement cutting-edge MLOps practices, and mentor colleagues by sharing expertise in cloud operations and ML engineering best practices.
• Manage GPU-powered Kubernetes clusters, improve automation pipelines, and ensure system reliability. Build and manage Kubernetes clusters from scratch, configuring them manually using tools like kubeadm, and deploy applications with Helm.

Qualifications

• MLOps & Kubernetes: GPU-enabled cluster management, built from scratch using kubeadm and Helm.
• Programming: Python or Go for ML automation workflows.
• Containerization: Docker and containerized application deployment.
• Cloud: AWS experience supporting ML workloads.
• CI/CD & Automation: ArgoCD, GitHub Actions, Infrastructure-as-Code (Terraform).
• Monitoring & Observability: Prometheus, Grafana, cloud-native stacks.
• ML Lifecycle: Production experience with experimentation, training, deployment, versioning, and monitoring.
• Reliability & Support: On-call participation, incident response, and system optimization.

Details

• Location: London (2x a week onsite)
• Day rate: £500 p/d (Outside IR35)
• Duration: 6-month