ml engineer for autonomous driving

Wayve develops Embodied AI technology for automated driving. Its AI software and foundation models enable vehicles to perceive, understand, and navigate complex environments, while its mapless and hardware-agnostic products support automakers in transitioning from assisted to automated driving. Gaia is Wayve’s video world model, trained on large-scale driving video to predict future frames and generate synthetic driving scenarios.

• Lead and execute large-scale training runs for video or adjacent foundation models, from experimental design through production-grade execution;
• Contribute to model architecture and training strategy using first-principles understanding rather than off-the-shelf application;
• Improve world-model capabilities for synthetic scenario generation and downstream evaluation and training of the driving model;
• Partner with research, applications, simulation engineering, and cloud/infrastructure teams to deliver end-to-end impact;
• Provide technical leadership through mentorship, review, and setting high engineering and research standards.

• In-depth experience training large-scale language, video, or other foundation models, including ownership of training at scale;
• Strong understanding of model architecture and the ability to contribute meaningfully to architectural and training decisions;
• Strong hands-on engineering skills with modern ML stacks such as PyTorch;
• Experience with debugging and performance- and reliability-minded development;
• Typically 4–5+ years of relevant industry experience;
• Nice to have: direct experience with world models, video generation, or long-horizon prediction, improving data and training pipelines, distributed training, efficiency, reliability, tech-lead ownership, mentoring, setting direction across an area.

• The role is based in an office in London;
• Hybrid working policy combines time in offices and workshops with time working from home;
• Advanced degrees are valued.