Rate: £600 per day (Outside IR35)
Contract Length: 3 Months
Location: Hybrid / Remote

We're supporting a business looking for an experienced MLOps Engineer to help scale and productionise machine learning solutions. You'll be responsible for building robust deployment pipelines, improving model monitoring, and ensuring ML systems are reliable, secure, and performant in production.

Key Responsibilities
Build and maintain ML deployment pipelines.
Develop CI/CD processes for machine learning models.
Implement model monitoring, observability, and alerting.
Manage cloud-based infrastructure and containerised environments.
Collaborate with Data Scientists and Engineers to productionise models.
Improve platform scalability, reliability, and automation.

Key Skills
Strong Python experience.
MLOps tooling (MLflow, Kubeflow, SageMaker, or similar).
Docker and Kubernetes.
CI/CD tooling (GitHub Actions, GitLab CI, Azure DevOps).
Cloud platforms (AWS, Azure, or GCP).
Infrastructure as Code (Terraform preferred).
Monitoring tools such as Prometheus or Grafana.

Contract: 3 Months | £600/day Outside IR35