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 behavioural 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. <|}
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