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Senior/Staff Machine Learning Engineer - AV Core Model Safety

wayve • United State
Visa Sponsorship Relocation
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Lead the technical direction and delivery of learned emergency manoeuvre prediction and collision detection models for autonomous vehicles. Own the full lifecycle from research to deployment, utilizing large-scale fleet data to validate capabilities and improve generalisation. Requires strong ML engineering expertise in Python and PyTorch with a track record of deploying real-world ML systems.

Key Highlights
Lead the development of end-to-end AV 2.0 models for emergency manoeuvre prediction and collision detection.
Drive the Core Model Safety roadmap, owning the full lifecycle from research to technology transfer.
Collaborate on online occupancy models and build high-value open-loop and closed-loop evaluations.
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 the global fleet.
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, working with AV Core, Evaluation, and Product Engineering on roadmaps and failure modes.
Maintain awareness of the wider business context, including division and company priorities and near-term product programmes.
Technical Skills Required
Python PyTorch Machine Learning
Benefits & Perks
Meaningful equity
Relocation support
Visa sponsorship
Hybrid working
Learning and development budgets
Comprehensive benefits including health insurance, dental, and enhanced parental leave
Nice to Have
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.
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) or vision-language-action models (VLA).
Proficiency in C++, CUDA, distributed training, or performance optimization for production machine learning systems.

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 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.
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