Research Scientist, Robot Foundation Model

Wayve•Sunnyvale, CA

7h•Hybrid

About The Position

Wayve is seeking a founding member for 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, aiming to create intelligent agents capable of perceiving, reasoning, moving, and manipulating in diverse embodiments. This role offers a unique opportunity to contribute to a new robotics program from its inception, working alongside experienced researchers in foundation models, embodied intelligence, and large-scale machine learning. The position involves meaningful ownership of research projects, influencing the team's technical direction, and testing ideas on real robotic systems. Responsibilities span the robot-learning stack, including developing model architectures and learning algorithms, building data and training pipelines, designing evaluations, and deploying policies on physical robots. The ultimate goal is to achieve strong research outcomes and develop increasingly general, robust, and useful real-world capabilities. Daily work may involve vision-language-action models, world and action models, multimodal and omni models, video models, reinforcement learning, imitation learning, and behavioral cloning. The role requires working with large-scale video and robotics datasets, distributed training infrastructure, and a fleet of robotic platforms, collaborating with scientists, ML engineers, roboticists, and hardware teams to translate concepts into large-scale experiments and demonstrations. This position provides substantial opportunities for learning and development in both frontier machine learning and real-world robotics, focusing on general robotics at the foundation-model frontier and shaping intelligent systems that interact with the physical world.

Requirements

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 run rigorous experiments 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 share research clearly across teams.

Nice To Haves

PhD or MS in Computer Science, Machine Learning, Robotics, Computer Vision or a related technical field.
Industry experience in machine learning, robotics, embodied AI or related applied research environments.
Experience with real robots, robotic learning, embodied AI, simulation or policy learning.
Experience working with large-scale video data and sequential decision-making systems.

Responsibilities

Research model 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.
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.