Principal Research Scientist, Robot Foundation Model

The Role

Wayve is seeking a Principal Research Scientist to join the Multi-Embodiment Generalist Agent (MEGA) team within Wayve Science. This team is focused on building foundation models for general-purpose robots beyond self-driving vehicles, creating intelligent agents that can perceive, reason, move, and manipulate the physical world across diverse embodiments. This is a senior, high-impact role with genuine 0→1 ownership, where you will help define the research agenda, technical strategy, and foundations of a new robotics program.

Key Responsibilities

• Lead research into architectures, data, and learning approaches for robot foundation models (e.g., VLAs, WAMs, omni-modal models, video models).
• Explore and develop learning approaches including reinforcement learning, behavioral 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 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.

About You (Essential Skills)

• Deep experience in machine learning, with a focus in one or more of: vision-language models, video models, robot policies, 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 (e.g., ICRA, CoRL, CVPR, NeurIPS, ICML, ICLR).
• Strong coding skills and hands-on experience with modern machine learning frameworks.
• Ability to design and drive an 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.

Desirable: PhD in Computer Science, Machine Learning, Robotics, Computer Vision or a related technical field; 5+ years of relevant industry experience; experience with real robots, robotic learning, embodied AI, simulation or policy learning; experience working with large-scale video data and sequential decision-making systems; experience mentoring researchers or leading technical workstreams.