Principal Machine Learning Engineer GAIA
About us
Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.
Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.
In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.
At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.
Make Wayve the experience that defines your career!
The role
Gaia is Wayve's world model: trained on large-scale driving video, it predicts future frames from past context functioning as a simulator that generates synthetic scenarios, and operating in closed loop with the driving model itself. As a Principal ML Engineer/ Applied Scientist, 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 focus areas are getting Gaia stable and coherent over long autoregressive rollouts, and making it reliably steerable towards the behaviours we need using signal from evaluation, and driving-model training.
Key responsibilities
Lead and execute Gaia's post-training and closed-loop pipeline, fine-tuning and aligning the world model through post-training experimentation and targeted data curation.
Push Gaia's autoregressive generation towards longer, more stable rollouts, and make the model deployment-ready, inference time and reliability included.
Contribute to broader model architecture and training-strategy decisions where they intersect with pre- and post-training and the application layer.
Partner closely with research, applications, simulation engineering, and cloud/infrastructure teams to translate post-training improvements into measurable downstream impact.
Provide technical leadership through mentorship, review, and setting high engineering/research standards.
About you — Essential
Hands-on experience post-training/fine-tuning large-scale models (language, video, or other foundation models)
Experience with world models, autoregressive generation, and long-horizon generation.
Experience with diffusion/flow models and understanding of 3D vision.
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 5+ years); advanced degrees are valued, but depth of applied experience is important
Desirable
Experience with inference optimisation or deploying large models under latency/compute constraints
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 role is a full-time role based in London, UK (hybrid). 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. We operate core working hours so you can determine the schedule that works best for you and your team.
Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know.
We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. 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.
At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.
For more information visit Careers at Wayve.
To learn more about what drives us, visit Values at Wayve
For US candidates only, please visit E-Verify Notice and Participation and Right to Work
DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.