Senior Machine Learning Operations Engineer (MLOPS)

Senior Machine Learning Operations Engineer (MLOPS)

Full-Time No working from home possible
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  • Location: Edinburgh or Glasgow or Alderley Park (Wilmslow)

  • Working Style: Hybrid 50% home/office based


We have an exciting opportunity for a experienced 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.


More About the role:



  • Design and evolve scalable, production-grade ML workflows on Databricks.

  • Lead effective use of MLflow for experiment tracking, model versioning, lineage and lifecycle management.

  • Build reusable CI/CD patterns for model training, validation, promotion and inference.

  • Champion strong engineering practices, including modular Python, testing, reproducibility and configuration management.

  • Work with data scientists and platform teams to productionise models safely and efficiently.

  • Mentor colleagues and support high standards across the team.


More about you:



  • Strong experience with Azure, including Azure ML, Data Factory and Azure DevOps.

  • Hands-on experience with Databricks, MLflow and production-grade ML workflows.

  • Advanced Python skills, with knowledge of SQL, Spark and testing approaches for ML.

  • Understanding of data engineering concepts such as ETL/ELT, feature stores and lineage tracking.

  • Awareness of security, governance, Responsible AI and relevant AI regulation.


About Royal London


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

  • private medical insurance


Inclusion, diversity and belonging


We’ re an inclusive employer and welcome applications from people of all backgrounds. We value the different perspectives, experiences and skills our colleagues bring.


Women in Data advertise roles on behalf of our partners, alliances, and members.


We are proud supporters of Women in Data. Connect, engage and belong to the largest free female data community in the UK – visit: www.womenindata.co.uk to join our community.


Stay connected! Follow us on LinkedIn for updates on career opportunities and more.

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Senior Machine Learning Operations Engineer (MLOPS) employer: Women in Data®

At Kingfisher, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters collaboration and innovation. As a Portfolio Strategy & Delivery Lead, you will have access to extensive growth opportunities within our technology sector, alongside competitive benefits that support your well-being. Our commitment to continuous improvement ensures that you will play a vital role in shaping the future of our business while working in a supportive environment that values your contributions.

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Contact Details:

Women in Data® Recruitment Team