OpenMind is building the operating system for robotics: the models that let robots understand people, context, and norms well enough to work alongside humans safely. Our research agenda spans social world models, vision-language-action systems, cross-embodiment learning, and multi-robot orchestration. Our work is deployed on real robots with real customers within weeks, not years.
You will define and execute research that ships. You will have access to a continuous stream of real-world embodied deployment data, including egocentric video, state-action logs, and human-robot interaction at scale.
Conduct original research on social world models, VLA architectures, and embodied reasoning, and drive it from idea to deployed system
Design data strategies that leverage our real-world deployment data for training and evaluation
Build rigorous evaluations for socially intelligent behavior, including simulation-based benchmarks and real-world measurement
Publish at top venues (CoRL, RSS, ICRA, NeurIPS) and represent OpenMind in the research community
Collaborate directly with our platform and deployment teams so research lands on physical robots quickly
MS or PhD in machine learning, robotics, or a related field, or equivalent research experience with a strong publication record
Deep expertise in at least one of: world models, VLA models, imitation or reinforcement learning, multimodal foundation models
Strong engineering fundamentals in languages such as Python, Go, and/or C++. You train your own models and write production-quality research code
A bias toward research that survives contact with the real world
First-author publications at CoRL, RSS, ICRA, ICML, NeurIPS, or ICLR
Experience deploying learned policies on physical hardware
Prior work at a frontier AI lab or leading robotics research group
| Location | San Francisco, California |
| Website | https://openmind.com/ |
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