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OXFIDA seeks a Senior Machine Learning Scientist to take technical ownership of CODAS research tracks and drive privacy-preserving generative AI initiatives. You will shape experiments, mentor junior scientists, and collaborate with Oxford/UCLA partners to produce deployable AI components.
Role offers hybrid work (Oxford office preferred, remote possible for the right candidate) on an 18-month fixed-term contract with potential extension or permanent move as funding allows.
OXFIDA (formerly 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 and researchers alongside commercial partners, and combining that expertise with real-world risk data at global scale to turn frontier research into AI that actually ships rather than just gets published.
Our work spans AI for insurance underwriting and claims, AI risk governance, privacy-preserving technologies for agentic AI, and quantum optimisation, alongside partnership projects on nature and supply chains and the emerging challenges nobody's solved yet.
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.
See risk clearly.
Fixed Term Contract: 18-month fixed-term contract from signing (running to March 2028), with a view to extending (to Sept 2029) or moving to permanent as a second round of programme funding is confirmed
Location: Oxford Office, Hybrid would be great but we are comfortable with fully remote for the right person.
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 and agentic 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 Scientist, you'll take technical ownership of research workstreams within CODAS. Rather than just executing a brief, you'll set the experimental direction yourself and push approaches like differential privacy, federated learning, and secure inference beyond what's already out there.
Bonus points: differential privacy or secure computation experience, LLM/agentic AI/frontier AI evaluation work, published research, or experience in regulated industries (insurance, financial services, public sector).