Staff Machine Learning Engineer (AV Core)

Wayve; United States; On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Private healthcare

Paid time off

Mental health resources

Community and socials

Competitive compensation

Learning and development

Job summary

Wayve is seeking a Staff Machine Learning Engineer to join the Core Model Safety team on AV Core. You will shape what our end-to-end driving model must understand to be safe and reliable and translate that into trained capabilities and adoption on the shared backbone across core and product engineering.

You will work with a senior, high-impact team, access to large-scale training and fleet data, and close partners in research, simulation, evaluation, and applied engineering to drive the roadmap

Qualifications

• 5+ years in ML engineering with pathfinding in ambiguous problems and knowledge transfer.
• Hands-on experience with transformer-based and multimodal architectures (VLM, VLA).
• Proficient in Python and other languages (C++, CUDA) and ML frameworks (PyTorch).
• Staff-level technical leadership: set direction and lead cross-functional work.
• Experience in 3D scene understanding and large-scale training with fleet data.
• Autonomous vehicles or robotics background with deployment and validation experience.

Responsibilities

• Shape the Core Model Safety roadmap from research to experiments and tech transfer.
• Train and deploy end-to-end AV 2.0 models on our global fleet with diverse data.
• Build evaluations for core capabilities and representation learning.
• Collaborate with research, simulation, evaluation, and engineering teams.
• Mentor others on the team and align priorities across AV Core and Product Engineering.

Skills

5+ years in ML engineering

Transformer-based architectures

Vision-language models

Python

C++

CUDA

PyTorch

Software engineering practices

Staff-level technical leadership

3D scene understanding

Large-scale training and fleet data

Tools

PyTorch

Python

C++

CUDA

Vision-language models

Job description

• As a Staff Machine Learning Engineer on Wayve’s Core Model Safety team in AV Core, you will help shape what our end-to-end driving model must understand to be safe and reliable in the real world - and turn that into trained capabilities, clear evidence, and adoption on the shared backbone across core and product engineering
• The Core Model Safety team builds foundational capabilities for assisted and automated driving - collision avoidance, scene understanding, 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
• 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 on our global fleet, using large-scale, diverse data to validate capabilities and improve generalisation across vehicles, markets, and driving conditions
• 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

Benefits

• Private healthcare: Choose our optional health insurance for comprehensive coverage for you and your family.
• Paid time off: Paid vacation plus public holidays and additional leave programs, ensuring you have time to unwind.
• Mental health resources: Through Spill, you can access therapy and mental health support.
• Community and socials: Join clubs or attend team socials to connect over hobbies, sports, or just for fun.
• Competitive compensation: Our compensation package includes cash and equity, making you a true partner in our success.
• Learning and development: Budgets for books, courses, and company-wide training to support your continuous growth.

Hands-on experience training shared representations with multiple tasks or objectives (multi-stage or joint training), including real trade-offs across data and losses5+ years in ML engineering, including pathfinding in ambiguous problems - from scoping and evals to establishing a direction (and knowledge transfer) for others to build onHands-on experience with transformer-based and multimodal architectures, including vision-language models (VLM), vision-language-action models (VLA), or equivalentProficient in Python and other relevant languages (e.g. C++ and CUDA) and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practicesStaff-level technical leadership: research-literate and pragmatic, setting direction, raising the bar, and leading cross-functional work without formal line managementWe understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to applyExperience in 3D scene understanding and representation learning for geometric and semantic perception, large-scale semantic enrichmentsPrior experience in autonomous vehicles or robotics with hands-on deployment and closed-loop validation on physical systemsExperience with redundant or fallback architectures, safety-critical systemsExperience across foundations/pretraining and applied engineering teams; large-scale training infrastructure and/or agentic workflowsExperience in reward modelling, behaviour modelling, model introspection, and/or interpretability