Member of Technical Staff, Robotics Engineer

About the role

Building general world models, systems that understand and simulate reality across tasks, modalities, and domains, requires closing the loop between learned representations and real-world action.

What you'll do

• Open to candidates based near our NYC office or those willing to relocate.
• Own the deployment loop for learned policies (VLAs, diffusion policies, World Action Models) on real robot arms: inference serving, action decoding, controller integration, latency budgets, and safety limits
• Diagnose real-world policy failures, determining whether the problem is data coverage, camera/proprioception mismatch, or execution, and partner with the research team to fix it at the right layer
• Design demonstration data collection protocols (task setup, camera placement, teleop conventions) that produce data our world models can actually learn from, working with our existing teleop and lab infrastructure
• Partner with research to run controlled experiments connecting world model representations, data composition, and fine-tuning recipes to physical success rates
• Define and run physical evaluation protocols so results are trustworthy and comparable across policy iterations
• Adapt our policy recipe to partner hardware and new embodiments

What they're looking for

• You have personally deployed software on real robot hardware and iterated to make it work, whether learned policies, motion planning, classical control, or perception-driven manipulation. You can walk through a specific...
• Fluency in the software-to-robot interface: action/command spaces, control frequencies, observation pipelines, calibration, and how each affects real-world behavior
• Comfort working at the intersection of software and physical systems: you can reconfigure a robot workspace and trace a policy failure in the same afternoon
• Bonus: direct experience deploying learned policies (VLAs, diffusion policies) on real hardware; experience with video/multimodal generative models or world models
• Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates.
• Great things come from great teams. We’d love to hear from you.

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