Principal Research Scientist, Robot Foundation Model

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. We build intelligent, mapless, and hardware-agnostic AI products designed for automakers, accelerating the transition from assisted to automated driving.

About 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 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 to work on compelling and publishable research while turning 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 real-world capabilities.

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, 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 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.

Requirements

• Deep experience in machine learning, with 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 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.

Qualifications

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

Pay

The reasonably estimated salary for this role ranges from $407,000 to $512,000, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.

Schedule

This is a full-time, hybrid role based in Sunnyvale, CA. We operate a hybrid working policy that combines time together in our offices and workshops with time spent working from home. We operate core working hours so you can determine the schedule that works best for you and your team.