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.
About our Engineering TeamThe
Core Model Safety team builds foundational capabilities for assisted and automated driving - collision avoidance, model understanding, and robustness under failure. You'll work in a focused, high-impact senior team with strong ownership, access to large-scale training and fleet data, and close partners in research, simulation, evaluation, and applied engineering.
Your day-to-dayAs a Senior/Staff Machine Learning Engineer in Wayve's AV Core organization, you will lead the technical direction and delivery of learned emergency manoeuvre prediction and collision detection models. Emergency manoeuvres are rare, high-consequence events that place unusual demands on data, modelling, and validation. You'll take the programme from problem definition through modelling, evaluation, integration, and evidence for deployment.
What you'll be working on- Drive Core Model Safety roadmap themes, owning the full lifecycle from research to offline/online experiments to technology transfer.
- Train and deploy end-to-end AV 2.0 models for emergency manoeuvre prediction and collision detection on our global fleet, using large-scale, diverse data to validate capabilities and improve generalisation across vehicles, markets, and driving conditions.
- Collaborate on online occupancy models for geometric and semantic perception.
- Build high-value open-loop and closed-loop evaluations for core capabilities and representation learning.
- Align priorities and learn from the organisation - with AV Core, Evaluation, and Product Engineering on roadmaps and failure modes; from fleet, simulation, and product feedback; and through mentoring others on the team.
- Maintain awareness of the wider business context - division and company priorities, near-term product programmes, and how Core Model Safety work enables them.
You should apply ifEssential- You have a strong track record of ML engineering, including pathfinding in ambiguous problems - from scoping and evals to establishing a direction (and knowledge transfer) for others to build on.
- You have hands-on experience with ML systems deployed in the real world.
- You're proficient in Python and PyTorch, with strong software engineering practices and hands-on experience building reliable machine learning training and evaluation systems.
- You have excellent experimental judgement: able to turn an ambiguous behavioral problem into falsifiable hypotheses, useful metrics, disciplined ablations, and clear technical decisions.
- You bring senior-level ownership and collaboration: able to lead a substantial technical area, work across research and engineering boundaries, and bring others along through clear written and verbal communication.
Desirable- Prior experience in autonomous vehicles or robotics with hands-on deployment and closed-loop validation on physical systems.
- Experience in 3D scene understanding and representation learning for geometric and semantic perception, large-scale semantic enrichments.
- Experience mining, generating, or evaluating rare events using simulation and fleet or heterogeneous real-world data.
- Experience with transformer-based and multimodal architectures, including vision-language models (VLM), vision-language-action models (VLA), or equivalent.
- Proficiency in C++, CUDA, distributed training, or performance optimization for production machine learning systems.
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.
How we work - Locations & Flexible Working:Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives.
The Interview Process:Our process is clear and respectful of your time:
- Initial call / recruiter screen [30 mins]
- Competency Interviews [hiring manager interview and applied ML interview; 2 hours total]
- Deep-dive technical interviews [programming, systems design, PyTorch debugging/ technical leadership interviews; 3 hours total]
- Final interview: mission & values alignment [Director or VP interview; 45 mins].
We'll always explain the format and work around your availability.
What's in it for you (Location dependant): Salaries benchmarked against the market annually
Meaningful equity, sharing in the ownership and long term success of Wayve
Relocation support and visa sponsorship where applicable
• Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
Learning and development budgets with support for training, conferences and growth
Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more
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.
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.
