Job Description
Senior Machine Learning Operations (MLOPS) Engineer
Contract Type: Permanent
Location: Alderley Park (Wilmslow)
Working Style: Hybrid - 50% from home / 50% office based
We have an exciting opportunity for a Senior Machine Learning Operations Engineer to join Royal London’s Group Data and AI Office. In this role, you’ll provide senior technical leadership for the workflows, tooling and engineering practices that take machine learning safely and reliably from experimentation into production.
Working closely with data scientists, data engineers and platform teams, you’ll define and evolve standards for CI/CD, experiment tracking, model lineage and controlled promotion across environments. Using Databricks, MLflow and Azure ML, you’ll help create scalable, well-governed pipelines that are reproducible, traceable and auditable.
You’ll also embed model risk management into delivery, supporting repeatable builds, clear lineage, transparent decision points and audit trails that strengthen governance and reduce operational risk.
As a senior practitioner, you’ll champion engineering excellence, reusable patterns and production-ready ways of working. You’ll mentor colleagues, support communities of practice and influence platform and architecture decisions so ML products deliver sustainable business value at scale.
If you feel you’d be a great fit for Royal London but don’t meet every requirement, we’d still love to hear from you!
We’re the UK’s largest mutual life, pensions and investment company, offering protection, long-term savings and asset management products and services.
Our People Promise is to make Royal London inclusive, responsible, enjoyable and fulfilling, underpinned by our Spirit of Royal London values: Empowered, Trustworthy, Collaborate and Achieve.
We offer great benefits, including 28 days’ annual leave plus bank holidays, up to 14% employer pension matching and private medical insurance.
We’re an inclusive employer and welcome applications from people of all backgrounds. We value the different perspectives, experiences and skills our colleagues bring.