At a Glance
- Tasks: Lead and improve large-scale machine learning models for self-driving technology.
- Company: Wayve, a pioneering company in autonomous driving solutions.
- Benefits: Private healthcare, paid time off, mental health resources, and competitive compensation.
- Other info: Join a collaborative team with opportunities for mentorship and professional growth.
- Why this job: Make a real impact on the future of self-driving cars in a fast-paced environment.
- Qualifications: Experience with large-scale models and strong engineering skills in modern ML stacks.
The predicted salary is between 70000 - 90000 £ per year.
Responsibilities
- 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.
- 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).
Benefits
- Private healthcare: Choose our optional health insurance for comprehensive coverage for you and your family.
- Paid time off: Paid vacation plus public holidays and additional leave programs, ensuring you have time to unwind.
- Mental health resources: Through Spill, you can access therapy and mental health support.
- Community and socials: Join clubs or attend team socials to connect over hobbies, sports, or just for fun.
- Competitive compensation: Our compensation package includes cash and equity, making you a true partner in our success.
- Learning and development: Budgets for books, courses, and company-wide training to support your continuous growth.
Qualifications
- In-depth experience training large-scale models (language, video, or other foundation models), including ownership of training at scale.
- 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.
- Strong understanding of model architecture and the ability to contribute meaningfully to architectural/training decisions.
- Experience improving data/training pipelines and working across infrastructure constraints (distributed training, efficiency, reliability).
- If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.
- Proven technical leadership (tech lead ownership, mentoring, setting direction across an area).
- Direct experience with world models, video generation, or long-horizon prediction.
We think you need these skills to ace Staff Machine Learning Engineer (Gaia)
Large-Scale Model Training
Video Generation
Model Architecture
Experimental Design
PyTorch
Debugging Skills
Performance Optimisation
