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# Senior Machine Learning Engineer

- **Company:** Aioi R&d Lab
- **Location:** Oxford, UK (Remote available)
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Continuous Integration, Linux, Python (Programming Language), Machine Learning, Azure Machine Learning, Large Language Models, Information Technology, Data Analytics, Machine Learning Operations, Software Version Control, Data Pipelines, Docker
- **Published:** September 14, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/senior-machine-learning-engineer/47162969

## About the Role

skills: clean, tested, well-documented code, not just working code. A track record of shipping ML/AI or data-driven systems into production or near-production environments. Solid experience with Linux, Docker, version control, CI/CD, and service-oriented deployment. The ability to work across the full lifecycle, from experimentation through to integration and operationalisation, and to mentor others along the way. Bonus points: generative AI/LLM application experience, privacy-preserving or compliance-sensitive systems work, multi-partner programme experience, or a background in regulated industries. You'll be the person turning frontier research into something that actually runs, with high ownership and high visibility. Real influence: the engineering standards and tooling you build become the Lab's default, not just your project's. Direct collaboration with Oxford researchers and international technology partners on a genuinely ambitious sovereign AI programme. This is
a fixed-term contract tied to CODAS's current funding cycle, but there's a genuine intent to extend and move roles to permanent as a second funding round is confirmed. It isn't a contract designed to end. #J-18808-Ljbffr

## Description

act as technical lead on how research gets built, tested, and shipped. What you'll do Lead the ML engineering and MLOps direction for assigned CODAS workstreams. Design, build, test, and maintain the ML services, data pipelines, evaluation tooling, and deployment-ready applications that make up the programme's technical deliverables. Translate research outputs into systems that are actually robust and maintainable, not just proofs of concept. Adapt AI/ML approaches for privacy-sensitive, security-conscious, regulated deployment contexts. Improve the Lab's internal tooling, engineering standards, and reusable frameworks: the kind of work that outlasts any one project. Mentor ML engineers and research associates, and communicate technical trade-offs clearly to non-technical stakeholders. What you'll bring A STEM degree (Computer Science, Maths, Stats, Physics, Engineering, or similar) or equivalent practical experience, plus 5+ years' relevant experience. Very strong Python engineering


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