Why This Role Stands Out
You will drive the technical direction for critical safety models in autonomous driving, gaining exposure to the full ML lifecycle on a global fleet. This role is ideal for experienced ML Engineers passionate about tackling complex, high-impact challenges and contributing to cutting-edge AI. Apply now to shape the future of safe autonomous systems!
Quick Overview
Job Description
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.
The role
As 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 will take the programme from problem definition through modelling, evaluation, integration, and evidence for deployment.
The Core Model Safety team builds foundational capabilities for assisted and automated driving - collision avoidance, model understanding, and robustness under failure. You will 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.
Key responsibilities
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.
About you
In order to set you up for success as a Staff / Senior Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.
Essential
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.
Hands-on experience with ML systems deployed in the real world.
Proficiency in Python and PyTorch, with strong software engineering practices and hands-on experience building reliable machine learning training and evaluation systems.
Excellent experimental judgement: able to turn an ambiguous behavioral problem into falsifiable hypotheses, useful metrics, disciplined ablations, and clear technical decisions.
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.
This is a full-time role based in our office in Sunnyvale. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. The reasonably estimated salary for this role ranges from $311,850 to $389,400, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.
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.
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