Research Scientist - Humanoid Robotics
Leads the research agenda for humanoid robotics, developing foundation-model and reinforcement-learning methods for dexterous manipulation and deploying them on real robotic systems. Requires a PhD, strong robotics research publications, and senior-level technical leadership.
About the job
Responsibilities
- Set and drive the research agenda for humanoid robotics, focusing on dexterous manipulation and frontier research problems.
- Conduct original research on world-action foundation models and reinforcement learning, delivering manipulation policies for humanoid robotic systems.
- Serve as a founding senior researcher, shaping the technical direction and growth of the team.
- Publish at top-tier venues such as CoRL, ICRA, and RSS.
- Collaborate with Research Engineers and product teams to deploy research into humanoid platforms and dexterous hands.
- Partner with senior researchers on cross-cutting autonomy and robotics problems.
Requirements
- 1+ years of industry research experience or a completed post-doc in a relevant field.
- Strong research record in robotics, manipulation, robot learning, or a related area, with publications in top-tier conferences or journals such as CoRL, RSS, ICRA, or IROS.
- PhD in machine learning, computer vision, robotics, or a closely related field.
- Strong technical convictions and a clear point of view on the field's direction.
- Ability to operate independently as a senior individual contributor and set direction for others.
- Passion for scalable, real-world robotics and physical AI.
Nice-to-haves
- Experience with humanoid robotics platforms, dexterous manipulation, or multi-fingered hands.
- Experience with VLA/WAM and post-training for robotics.
- Experience with large-scale reinforcement learning in robotic simulation and sim-to-real transfer.
- Experience with imitation learning from teleoperation or human demonstration data.
- Prior tech lead or founding-team experience.
Skills
Robotics, Humanoid Robotics, Dexterous Manipulation, Robot Learning, Reinforcement Learning, Machine Learning, Computer Vision, World-Action Foundation Models, Sim-To-Real Transfer, Imitation Learning, Teleoperation, Corl, Icra, Rss, Iros
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