Principal Research Scientist, Robot Foundation Models

Overview

As a founding Principal Research Scientist on the MEGA team, you define the research agenda and technical strategy for robot foundation models. You shape architectures, data strategies and learning methods across vision-language-action, world models and policy development. You collaborate with scientists, engineers and hardware teams to translate research into real-world robot capabilities. This role offers ownership from 0-to-1 and impact on scalable, multi-embodiment robotics.

Pay / Benefits

• salary commensurate with market
• meaningful equity
• relocation support and visa sponsorship
• hybrid working
• learning and development budgets
• comprehensive benefits including health and wellbeing

Responsibilities

• Lead research on architectures, data and learning methods for robot foundation models
• Design, implement and evaluate models such as VLAs, WAMs, omni-modal and video models
• Explore RL, behavioural cloning and related policy-learning approaches
• Synthesize and curate large video datasets for training and evaluation
• Build and optimize scalable distributed training pipelines and infrastructure
• Influence robot policy development and data strategy
• Collaborate with scientists, engineers and robotics teams to connect research to performance
• Communicate research findings internally and contribute to external publications

Key requirements

• Deep experience in machine learning with emphasis on vision-language models, video models, robot policies or robotics foundation models
• Experience with scalable training on large datasets and models
• Strong research track record with publications in top venues (e.g., ICRA, CoRL, CVPR, NeurIPS, ICML, ICLR)
• Strong coding skills and hands-on ML framework experience
• Ability to drive an independent research agenda while collaborating with engineering and robotics teams
• Experience translating ideas into working systems, experiments or deployed capabilities
• Strong communication skills and ability to influence technical direction across teams

• Strong communication
• Cross-team collaboration
• Strategic thinking
• Vision-language models
• Video models
• Robot policies

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