Gaia is Wayve’s video world model: trained on large-scale driving video, it predicts future frames from past context—functioning as a simulator that helps generate synthetic scenarios, including rare or safety-critical events. As a Staff ML Engineer on Gaia, you’ll own and drive work on training and improving frontier-scale models trained in-house. This is a high-impact role with the opportunity to tech-lead a key area and help shape the next version of Gaia in a fast-paced, results-focused environment.
Key responsibilities:
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 that enable synthetic scenario generation and downstream evaluation/training of the driving model
Partner closely 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/research standards (Senior/Staff scope)
In order to set you up for success as a Staff ML Engineer (Gaia) at Wayve, we’re looking for the following skills and experience.
Essential
In-depth experience training large-scale models (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/training decisions
Strong hands-on engineering skills with modern ML stacks (e.g., PyTorch), including debugging and performance/reliability-minded development
Relevant industry experience (typically 4–5+ years); advanced degrees are valued, but depth of applied experience is important
Desirable
Direct experience with world models, video generation, or long-horizon prediction
Experience improving data/training pipelines and working across infrastructure constraints (distributed training, efficiency, reliability)
Proven technical leadership (tech lead ownership, mentoring, setting direction across an area)
This is a full-time role based in our office in London. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.
Job details are sourced from the employer's original posting.
Open job postingAbout the company
Wayve is building the next generation of autonomous driving technology. They are developing an end-to-end autonomous driving system that uses deep learning and AI to enable vehicles to navigate roads and environments.