Lead Machine Learning Engineer

Senior Machine Learning Scientist

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.

Contract: Permanent

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

The role

This is a genuine dual role: real line management and delivery leadership across the Lab's ML engineering function, plus a meaningful hands-on contribution to technical delivery yourself. You'll manage a growing team of ML Engineers and Scientists, shape ML engineering practice across the Lab, and stay close enough to the work to actually lead it technically, not just report on it.

What you'll do

• Line-manage and develop ML engineers: coaching, mentoring, feedback, and input into hiring and onboarding.
• Stay hands-on with technical delivery on selected projects, alongside your leadership responsibilities across multiple engagements.
• Work with the Lead ML Scientist and Principal Engineer to build ML engineering best practice across the Lab.
• Work closely with the Project and Account Management teams to design and scope ML solutions that drive value for our customers.
• Lead multidisciplinary teams of ML engineers, scientists, and software engineers, and support solution design so systems are robust and scalable.
• Provide oversight and quality assurance across concurrent projects, flagging technical and delivery risks early.
• Lead use case discovery and support pre-sales work alongside the commercial team.
• Drive reuse of shared frameworks and standards across projects, and communicate technical risk clearly to non-technical stakeholders.

What you'll bring

• A STEM degree or equivalent practical experience, plus 7+ years in ML engineering, software engineering, or a related technical role, including experience leading technical work across teams.
• A strong software engineering background with real production-system delivery experience.
• Experience managing or leading ML engineers or technical contributors in a delivery-focused setting.
• Comfort supporting pre-sales or technical discovery work alongside commercial teams.
• The judgement to lead solution design and assure engineering quality without being the primary hands-on contributor on every project.
• Strong communication skills: you'll need to challenge stakeholder expectations sometimes, not just relay them.

Bonus points: experience establishing ML engineering/MLOps best practice from scratch, background in regulated or enterprise environments, or a track record of driving reuse through shared frameworks and tooling.

Why join us

• This is a genuine build-it role: shape how ML engineering is done as the Lab scales up its delivery capability.
• You'll stay technical. This isn't a management role that pulls you away from the work, it's built to keep you in it.
• Direct line to the Director of AI Delivery and real input into use case shaping and pre-sales, not just delivery execution.
• Permanent role, real team, real influence over how the Lab's engineering function grows from here.