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Salary
≈ $168k – $373k per year (Estimated)
Location
In office (San Francisco)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 28, 2026. First seen by Alion on Aug 12, 2026.

Overview
Company
Impact
Profile match
OpenMind is the AI brain and infrastructure layer for teams of robots in human-facing environments such as factories, retail stores, hospitals and the field. It builds the models and operating system that let robots understand people, context and norms and runs them on real robots with customers, and it hires machine learning, robotics, reliability and forward deployed engineers. The company is headquartered in San Francisco, California, United States.
Backed by Faction, Pebblebed

The Role

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.

What You Will Do

  • 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

What We Look For

  • 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

Nice to Have

  • 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

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