SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Wayve is building embodied AI for autonomous vehicles and robotics. You will join the Multi-Embodiment Generalist Agent (MEGA) team as a founding Research Scientist, working on foundation models for general-purpose robots that learn from large-scale video, language, and robot-interaction data and generalize across tasks and embodiments (mobile manipulators, dual-arm platforms, humanoids).
Your day-to-day work will include:
- Designing and running experiments on model architectures, learning objectives, and data strategies for robot foundation models
- Building scalable pre-training and post-training methods using web video, egocentric video, and robot-interaction data
- Curating, filtering, mixing, and evaluating large robotics datasets (egocentric, UMI, teleoperated)
- Developing and using distributed training pipelines for large multimodal models
- Partnering with ML engineers, roboticists, and hardware teams to translate research into measurable real-world robot performance
- Communicating findings through internal reviews, publications, and robot demonstrations
You will work on research and development of model architectures, learning objectives, and data strategies; scalable self-supervised and generative pre-training methods; post-training approaches including supervised fine-tuning, imitation learning, and reinforcement learning; large-scale dataset curation and evaluation; and distributed training infrastructure. The role combines frontier ML research with direct evaluation on a growing fleet of robots. Work may span vision-language-action models, world and action models, video and multimodal models, imitation learning, reinforcement learning, and self-supervised learning.
Wayve operates a hybrid model with main hubs in London, Sunnyvale, Yokohama, Herzliya, Vancouver, and Leonberg. The company is pioneering an end-to-end AI approach for autonomous driving that enables vehicles to learn from real-world experience, adapt, and generalize at scale.
REQUIREMENTS:
- Experience in machine learning with a focus on multimodal foundation models and data for foundation models
- Experience with scalable training (multi-node training, large datasets, large model training)
- Strong research track record with publications in top-tier venues (ICRA, CoRL, CVPR, NeurIPS, ICML, ICLR)
- Strong engineering skills and hands-on experience with modern machine learning frameworks
- Ability to design and run rigorous experiments while collaborating with engineering and robotics teams
- Experience translating research ideas into working systems, experiments, or deployed capabilities
- Strong communication skills and ability to share research clearly across teams
Note: The posting encourages applications from those passionate about autonomy even if not meeting every requirement.
