Machine Learning Scientist/Engineer

Wayve • Sunnyvale, CA

1d • $311,450 - $419,760 • Hybrid

About The Position

We are looking for a 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: models that learn from large-scale video, language, and robot-interaction data, then generalize across tasks and embodiments, including mobile manipulators, dual-arm platforms, and humanoids. Our aim is to build agents that can perceive, reason about, and act reliably in the physical world. You will help define and build the foundation-model learning stack for robotics: novel model architectures, pre-training objectives, post-training methods, and scalable data and training systems. The work combines frontier ML research with a direct route to real-world evaluation on a growing fleet of robots. Your work may span vision-language-action models, world and action models, video and multimodal models, imitation learning, reinforcement learning, and self-supervised learning. You will work with large-scale video and robotics datasets and distributed training infrastructure to develop increasingly capable, robust, and general robot policies. You will collaborate with research scientists, ML engineers, roboticists, and hardware teams to turn promising ideas into large-scale experiments, strong research contributions, and compelling robot demonstrations.

Requirements

• Experience in machine learning, with a focus on multimodal foundation models and data for foundation models.
• 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 engineering 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.

Responsibilities

• Design and run experiments on model architectures, learning objectives and data strategies for robot foundation models.
• Build scalable pre-training and post-training methods using web video, egocentric video and robot-interaction data.
• Curate, filter, mix and evaluate large robotics datasets, including egocentric, UMI and teleoperated data.
• Develop and use distributed training pipelines for large multimodal models and datasets.
• Partner with ML engineers, roboticists and hardware teams to turn research progress into measurable real-world robot performance.
• Communicate findings through rigorous internal reviews, publications and robot demonstrations.
• Research and develop model architectures, learning objectives, and data strategies for robot foundation models.
• Develop scalable self-supervised and generative pre-training methods using web video, egocentric video, and robot-interaction data.
• Develop post-training approaches, including supervised fine-tuning, imitation learning, reinforcement learning, and related methods, to improve real-world robot capabilities.
• Curate, filter, and evaluate large-scale robotics datasets, including egocentric, UMI, and teleoperated data.
• Build and use distributed training pipelines for large models and large multimodal datasets.
• Work closely with robotics and hardware teams to connect model progress to measurable real-world performance.
• Communicate research clearly internally and, where appropriate, through publications and Wayve’s scientific presence.

Benefits

• Salaries benchmarked against the market annually
• Meaningful equity, sharing in the ownership and long term success of Wayve
• Relocation support and visa sponsorship where applicable
• Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
• Learning and development budgets with support for training, conferences and growth
• Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed