Principal Research Scientist, Robot Foundation Model

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 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 0-1 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. The goal is work on compelling and publishable research, but also to turn it into systems that demonstrate increasingly general, robust and useful behavior in the physical world. 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 work with large-scale video and robotics datasets, distributed training infrastructure and a growing fleet of physical platforms. 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. This is a rare opportunity to help build a general robotics effort from the ground up—combining frontier foundation-model research with the immediacy and complexity of intelligence embodied in real machines. Key Responsibilities 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. About You In order to set you up for success as a Principal Research Scientist at Wayve, we’re looking for the following skills and experience. E #J-18808-Ljbffr EngineersOfAI