Staff / Senior Machine Learning Engineer, AV Core
$312k - $389k • Sunnyvale, California USA • Full-time
Posted 25d ago
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
Wayve is building the leading AI platform for autonomous driving, pioneering an end-to-end AI approach that enables vehicles to learn directly from real-world experience. This role is within the Core Model Safety team, which builds foundational capabilities for assisted and automated driving, focusing on 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.
As a Senior/Staff Machine Learning Engineer, you will lead the technical direction and delivery of learned emergency manoeuvre prediction and collision detection models. These are rare, high-consequence events that place unusual demands on data, modelling, and validation. You will take the program from problem definition through modelling, evaluation, integration, and evidence for deployment, driving core model safety roadmap themes and owning the full lifecycle from research to offline/online experiments to technology transfer.
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.
- 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 organization, including AV Core, Evaluation, and Product Engineering.
- Maintain awareness of the wider business context and how Core Model Safety work enables company priorities.
Requirements
- Strong track record of ML engineering, including pathfinding in ambiguous problems.
- Hands-on experience with ML systems deployed in the real world.
- Proficient in Python and PyTorch, with strong software engineering practices.
- Experience building reliable machine learning training and evaluation systems.
- Excellent experimental judgement to turn ambiguous problems into falsifiable hypotheses and clear technical decisions.
- Senior-level ownership and collaboration skills.
- Prior experience in autonomous vehicles or robotics with hands-on deployment and closed-loop validation on physical systems (desirable).
- Experience in 3D scene understanding and representation learning (desirable).
- Experience mining, generating, or evaluating rare events using simulation and fleet data (desirable).
- Experience with transformer-based and multimodal architectures, including vision-language models (VLM) or equivalent (desirable).
- Proficiency in C++, CUDA, distributed training, or performance optimization for production ML systems (desirable).