Principal Research Scientist, Robot Foundation Models
Before the detail, here's the challenge you'd help us solve.
We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.
Here’s what this particular role covers.
🛠️ About our Science Teams
We are looking for a Principal Research Scientist to join the Multi-Embodiment Generalist Agent (MEGA) team within Wayve Science as a founding member. MEGA is building foundation models for general-purpose robots beyond self-driving vehicles. Our focus is on creating intelligent agents that can perceive, reason, move and manipulate the physical world across diverse embodiments, including mobile manipulators, dual-arm platforms and humanoids. This is a senior, high-impact role with genuine 0-to-1 ownership. You will help define the research agenda, technical strategy and foundations of a new robotics program, working alongside world-class researchers in foundation models, embodied intelligence and large-scale machine learning. You will have the opportunity to work across the entire robot-learning stack: building scalable data flywheels, developing new model architectures and learning algorithms, training large models, designing rigorous evaluations and deploying policies on real robots. Your day-to-day work may span vision-language-action models, world and action models, multimodal and omni models, video generation, reinforcement learning, imitation learning and behavioral cloning. You will collaborate closely with researchers, ML engineers, roboticists and hardware teams to move ambitious ideas rapidly from research hypotheses to large-scale experiments and impressive real-world capabilities.
🧠 Your day-to-day
Research in architectures and data around robot foundation models.
Implement and experiment with different models such as VLAs, WAMs, omni models, and video models.
Implement and experiment with different learning approaches of the RL/BC kind.
Synthesize and filter large video datasets.
Build scalable distributed training pipelines and infrastructure.
Influence and/or own robot policy development and data decisions.
🧩 What you’ll be working on
Lead research into architectures, data and learning approaches for robot foundation models.
Design, implement and evaluate models such as VLAs, WAMs, omni-modal models, video models and related foundation-model architectures for robotics.
Explore and develop learning approaches including reinforcement learning, behavioural cloning and other methods relevant to robot policy development.
Synthesize, curate and filter large-scale video datasets for model training and evaluation.
Build and use scalable distributed training pipelines and infrastructure for large models and large datasets.
Influence and/or own technical decisions around robot policy development, data strategy and model design.
Collaborate closely with scientists, engineers and robotics teams to connect research progress to real-world robot performance.
Communicate research clearly internally and, where appropriate, contribute to external publications and Wayve’s scientific presence.
🙌 You should apply if
Deep experience in machine learning, with a focus on one or more of: vision-language models, video models, robot policies, or foundation models for robotics or embodied AI.
Experience with scalable training, such as multi-node training, large datasets and/or large model training.
Strong research track record, including publications in top-tier venues such as ICRA, CoRL, CVPR, NeurIPS, ICML or ICLR.
Strong coding skills and hands-on experience with modern machine learning frameworks.
Ability to design and drive an independent research agenda while collaborating closely with engineering and robotics teams.
Experience translating research ideas into working systems, experiments or deployed capabilities.
Strong communication skills and the ability to influence technical direction across teams.
🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement.
More about Wayve:
🚀 Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines.
Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility.
How we work 💻- Locations & Flexible Working:
Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives.
🔍 The Interview Process:
Our process is clear and respectful of your time:
Initial call / recruiter screen (30 mins)
Competency Interviews (Pytorch Debugging and hiring manager interview; 1.5 hours total)
Deep-dive technical interviews (Systems & domain-specific interviews; 3 hours total)
Final interview: Mission & values alignment (45 mins)..
We’ll always explain the format and work around your availability.
What’s in it for you (Location dependant):
💰 Salaries benchmarked against the market annually
📈 Meaningful equity, sharing in the ownership and long term success of Wayve
✈️ Relocation support and visa sponsorship where applicable
✅ Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
📚 Learning and development budgets with support for training, conferences and growth
🩺 Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more
A quick, honest note before you apply.
Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one.
If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you.
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
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.
