Lead R&D efforts to prototype a new robotic manipulator, conducting rigorous testing to validate design specifications and performance criteria, focusing on automating industrial processes using advanced robotics and AI.
Responsibilities
Lead R&D efforts to prototype a new robotic manipulator
Work with industry-standard hardware platforms to develop and deploy robotic manipulators for real world testing
Develop and implement models for hybrid dynamical systems exhibiting both continuous and discrete dynamic behaviors
Design advanced planning algorithms to optimize manipulation tasks such as pick-and-place operations
Experience with supervised learning, unsupervised learning, and reinforcement learning techniques to improve manipulation performance in robots
Requirements
Ph.D. in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or related field, with a strong emphasis on robotics
Conduct original research in embodied AI, robotic manipulation, and world modeling—including perception, planning, and control.
Compensation
Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, or relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only. It does not include discretionary bonus, equity, or benefits.
Responsibilities
Conduct original research in embodied AI, robotic manipulation, and world modeling—including perception, planning, and control.
Develop and evaluate large-scale multimodal models that integrate vision, language, proprioception, and tactile inputs for real-world robotic tasks.
Create and prototype algorithms for dexterous robotic hands, contact-rich manipulation, and adaptive task generalization.
Explore methods for sim-to-real transfer, self-supervised physical interaction learning, and reinforcement learning in dynamic environments.
Collaborate with hardware and systems teams to translate research into real robotic systems—from simulation to physical deployment.
Requirements
Master’s or Ph.D. in Robotics, Computer Science, Artificial Intelligence, Mechanical/Electrical Engineering, or related fields.
Nice to have: Ph.D. (or Ph.D. candidate expecting graduation within 6–12 months).
Nice to have: Track record of publications in top AI or robotics conferences (CoRL, ICRA, IROS, RSS, NeurIPS, CVPR, ICML).
Design and implement advanced robot learning models and training procedures to achieve dexterous manipulation for humanoid robots with high DOF and multi‑fingered hands.
Own the ML manipulation pipeline and roadmap, combining different learning paradigms to achieve real‑world, industrial‑level robustness.
Work with the Teleoperation and Data team to design data collection, sensor modularity, and data mixture strategies.
Leverage existing state‑of‑the‑art manipulation models and contribute to the development of new architectures for emerging complex tasks.
Deploy trained manipulation models to robotic hardware, ensuring real‑time performance, safety, and integration with control systems and sensors.
Lead closed-loop simulation for robotics, autonomy, perception, planning, controls, and machine systems, bridging virtual environments with production robotics software and physical-machine testing.
Compensation
$147,760.00 - $240,110.00
Responsibilities
Define the technical architecture for robotics and Physical AI simulation.
Build closed-loop environments for autonomous and semi-autonomous machines.
Lead Software-in-the-Loop, Hardware-in-the-Loop, and Vehicle-in-the-Loop strategies.
