Senior Machine Learning Engineer

Aioi R&D Lab – Oxford is an AI R&D company based in Oxford, on a mission to harness AI to understand, predict, and manage risk, helping build a safer, more resilient society.

We sit at the intersection of academia and industry, working with Oxford's professors, researchers, and graduates alongside commercial spinouts and partner companies, to turn frontier research into AI that actually ships rather than just gets published.

Our work spans applied AI for insurance and adjacent industries, including supply chains, nature, autonomous driving, and the emerging challenges nobody's solved yet, alongside deep research of our own into agentic AI, privacy-preserving technologies, trustworthy AI, complex systems modelling, and quantum computing.

We build AI products and solutions for insurers, businesses, and public-sector organisations worldwide, and run innovative research projects that push these technologies further, helping people make better decisions in an uncertain world.

Fixed Term Contract: 18-month fixed-term contract from signing (running to at least Feb 2028), with a view to extending (to 3 years) or moving to permanent as a second round of programme funding is confirmed

Location: Oxford, hybrid preferred, though we'd consider fully remote for the right person

The role

You'd be joining CODAS, our flagship sovereign AI programme, built in partnership with Japanese public and private sector organisations and academic collaborators at Oxford and UCLA. The goal is a privacy-preserving generative AI ecosystem that protects personal and sensitive data by design, through data residency, anonymisation, secure deployment, and privacy techniques that hold up at both training and inference time.

As a Senior Machine Learning Engineer your job is to take what the research side proves works and turn it into something dependable enough to run in a live, privacy-sensitive, multi-partner environment. You'll set the ML engineering and MLOps direction for your workstreams and 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 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.

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