MLOps Engineer

MLOps Engineer

Contract

London based (hybrid or onsite depending on preference)

Outside IR35

£600 to £650 per day

I am supporting a client in London who is preparing to scale their machine learning capability. They need an experienced MLOps Engineer who can take models from development into a reliable production environment and keep everything running smoothly throughout the life cycle.

What you will be working on

Building, improving and maintaining the end to end ML pipeline from data ingestion through to deployment.

Working closely with Data Scientists to turn notebooks and prototypes into production ready workloads.

Setting up CI and CD for model training, testing and deployment using Python based toolsets.

Managing model performance, drift monitoring and regular retraining workflows.

Creating infrastructure using Terraform or similar, ideally within Azure.

Maintaining containerised workloads using Docker and Kubernetes.

Supporting observability by putting in place clear logging, alerting and metrics for ML services.

Ensuring best practice for version control, experiment tracking and model registry.

Troubleshooting production issues and improving stability and performance across the ML platform.

Key skills

Strong Python for production environments.

Solid experience with Azure for ML workloads including compute, networking and storage.

Good knowledge of MLOps tools such as MLflow, Azure ML, Kubeflow or similar.

Strong background in CI and CD using GitHub Actions, Azure DevOps or similar.

Experience working in containerised environments using Docker and Kubernetes.

Clear understanding of how to support Data Scientists and engineering teams through the model life cycle.

Useful to have

Experience working on large scale data or ML projects.

Good understanding of data engineering fundamentals.

Experience working in regulated or high availability environments.

If you're an experienced MLOps Engineer feel free to apply or send your C.V

MLOps Engineer