Machine Learning Engineer, Driving Product
London, England, United Kingdom Full-time Posted 49 minutes ago
We are hiring Senior and Staff ML Engineers that sit within Driving Product organisation, building critical behaviours for Level 2 to level 4 driving. It is highly product-focused: you will train and iterate on end-to-end driving models and get them shipped into the car on a fast timeline measured in months. The opportunity is to own the full loop from data and training through evaluation and on-road validation, with direct impact on high-priority commercial deliveries (including the Nissan production and Robotaxi). You will join a small, high-ownership teams at the point of rapid growth, where execution and real-world outcomes matter.
Key Responsibilities
In order to set you up for success as a Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.
Key Responsibilities
- Develop the AI driver model architecture and training algorithms to introduce and enhance the driving behaviors for L2/L3/L4
- Own key parts of the training model lifecycle, including evaluation strategy, success metrics, and iteration planning.
- Mine, bucket, and curate real-world and synthetic data to teach specific driving behaviours, and implement data schemes to support training.
- Run and analyse on-road and offline experiments, translate results into clear next steps, and drive improvements through repeated training cycles.
- About you
In order to set you up for success as a Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.
- Essential
- Proven experience training deep learning models, with clear end-to-end ownership (data, training, evaluation, iteration).
- Experience taking ML models into production, including working through real-world constraints and quality and safety requirements
- Reinforcement learning experience (especially where it materially improved real-world performance).
- Experience with end-to-end driving models and / or transformer networks
- Automotive or OEM experience, or prior work that involved deploying ML into physical systems.
- Experience with a Pytorch lightning training infrastructure
- Experience with model compression and deployments to embedded systems