We’re seeking an exceptional Roboticist / Robotic Systems Engineer to build and deploy robotic embodiments for embodied AI research, integrating hardware and software to run VLMs and VLAs, enable teleoperation and data collection, and support rapid iteration between real-world robots and learning systems.
As a Robotic Systems Engineer on our team, you’ll own the full lifecycle of embodied platforms used for research. You’ll help bring up new robot embodiments, integrate learning-based models, and create the infrastructure that enables rapid iteration between robot deployment, data collection, model training, and evaluation.
Your work will span:
Robotic Embodiments & Integration
Build, integrate, and deploy open- and closed-source robotic platforms, spanning actuation, sensing, compute, and software stacks
VLM / VLA Deployment
Deploy and evaluate vision-language models (VLMs) and vision-language-action models (VLAs) on real robotic systems, including adapting open-source VLAs such as GR00T, OpenVLA, and related frameworks to new embodiments and tasks
Simulation & Model-in-the-Loop Development
Use simulation environments such as Isaac Sim to develop, test, and validate robotic behaviors, and to support sim-to-real iteration
Teleoperation & Data Collection Systems
Design and implement teleoperation and mixed-autonomy systems—including VR/MR-based interfaces (e.g., Apple Vision Pro, Meta Quest 3)—to enable scalable, high-quality robot data collection
Controls, Autonomy & Feedback
Implement and tune control, state estimation, and autonomy components that support stable, repeatable robot behavior in real-world environments
Reliability, Observability & Debugging
Build tooling, diagnostics, and processes that maximize robot uptime and accelerate debugging across mechanical, electrical, firmware, and software layers