For researchers, this means an opportunity to:
- Work on fundamental challenges in robotics and AI: multimodal learning, tactile-rich manipulation, sim-to-real transfer, and large-scale benchmarking.
- Access state-of-the-art infrastructure: hundreds of humanoid robots, GPU clusters, high-fidelity simulators, and a global-scale evaluation pipeline.
- Collaborate with leading experts across academia and industry, and publish results that will shape the next decade of robotics.
- Contribute to an initiative that will redefine the future of embodied AI—with all results made open to the world.
As we prepare for our official launch on October 1, 2025, we are assembling a world-class team ready to pioneer the next era of robotics.
We invite ambitious researchers and engineers to join us in this bold challenge to rewrite the history of robotics.
Responsibilities
- Designing and building scalable data collection systems that operate across hundreds of humanoid and mobile robots.
- Developing semi-autonomous teleoperation systems that ensure low latency, high controllability, and minimal operator workload.
- Creating automated pipelines to deploy trained models and rigorously evaluate them in both simulation and real-world robotic platforms.
- Working closely with the Vision-Language-Action (VLA) team to seamlessly integrate and deploy cutting-edge models onto physical robots.
Requirements
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Ph.D. in Robotics, Mechanical Engineering, Computer Science, or a related field, or M.S. with 3+ years of equivalent industry or research experience.
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Extensive hands-on experience with physical robotic platforms (e.g., mobile robots, manipulators such as UR5, Franka Emika, HSR, or humanoids like Spot).
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Demonstrated ability to control real robots using ROS / ROS2, including full-stack integration and deployment.
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Solid understanding and implementation experience in teleoperation, AR/VR interfaces, and leader–follower architectures.
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Strong programming proficiency in C++ and Python, with ability to contribute production-level code and perform system-level integration.
- Proven ability to work both independently and collaboratively in multidisciplinary research and engineering teams.
- Note:
- Candidates focused solely on theoretical research (e.g., reinforcement learning or explainable AI) without practical robotics experience will not be considered.
- However, candidates do not necessarily need to meet every single qualification to be considered for this role.
Nice to haves
While not specifically required, tell us if you have any of the following.
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Publication record in top-tier robotics conferences or journals (RSS, CoRL, ICRA, IROS, TRO, IJRR).
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Publications limited to CVPR, ICCV, or NeurIPS could be considered AI-centric and scored lower for this position.
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Experience implementing advanced control strategies on hardware (impedance control, force/torque control, admittance control, or model predictive control).
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Practical experience with tactile sensing or contact-rich manipulation.
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Experience leading or contributing to large-scale robot data collection or fleet management systems.
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Familiarity with robotic simulators (Isaac Sim, MuJoCo, or PyBullet) for training and evaluation.
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Experience integrating Sim2Real transfer or Vision–Language–Action (VLA) models onto real robotic systems.
