Manager, Machine Learning, Vision Models

Before the detail, here's the challenge you'd help us solve.

We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.

Here’s what this particular role covers.

Wayve’s engineering teams are building the AI, robotics, simulation, data, and systems foundations needed to deploy a generalisable AI Driver safely and at scale.

The Measurement team within AI Evaluation builds and productionises the offline scene-understanding models that measure driving performance after on-road runs and in simulation. The team adapts on-vehicle and foundation-model technology to exploit the greater compute, model capacity, and temporal context available offline.

• Lead and develop a London-based team of Senior Machine Learning Engineers while remaining deeply engaged in technical direction.
• Set the architecture for robust, scalable offline scene-understanding and measurement models.
• Translate ambiguous business goals into sprint, quarterly, annual, and multi-year technical roadmaps.
• Review designs and code, raise the engineering quality bar, and ensure models are reliable enough for customer-facing deliverables.
• Align roadmaps across on-vehicle modelling, foundation models, Evaluation, Simulation, and Model Development Platform teams in the UK and US.
• Identify capability gaps ahead of demand and build the technical and organisational case to address them.
• Offline models that predict and explain counterfactual driving outcomes.
• Scene-understanding systems that assess coverage, mine rare events, and measure learned driving behaviour.
• Rig-agnostic architectures built from transformer, multimodal, and foundation-model technology.
• Production ML systems that shorten the loop between driving-model changes and reliable evaluation evidence.
• A growing senior team operating across multiple organisations and locations.

🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement.

More about Wayve

🚀 Wayve is building the leading AI platform for autonomous driving. We are pioneering an end-to-end AI approach that enables vehicles to learn directly from real-world experience, developing the ability to adapt, generalise and improve at scale.

Our ambition is to make autonomy universal. Wayve’s mapless and hardware-agnostic AI platform integrates with global OEM partners, enabling continuous software evolution from L2+ through to L4.

How we work 💻 — Locations & Flexible Working

This role is based in London. We operate a hybrid model combining in-person collaboration in our offices and workshops with focused time working remotely.

🔍 The Interview Process

We’ll always explain the format and work around your availability.

A quick, honest note before you apply.

Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one.

If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you.

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

For more information visit Careers at Wayve. To learn more about what drives us, visit Values at Wayve

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.