Senior Embodied AI Engineer - Controls

Responsibilities

• Automate, develop, implement, and validate advanced control and learning algorithms for real‑world embodied robotic systems.
• Design and conduct experiments to expand control robustness, precision, and adaptability across diverse tasks and environments.
• Combine classical and learning‑based control methods (e.g., MPC, IL, RL) for scalable and reliable skill acquisition.
• Collaborate with perception and systems engineers to integrate AI control stacks into production platforms.
• Leverage simulation, digital twins, and expert demonstrations to accelerate control policy development and deployment.
• Stay up-to-date on cutting‑edge research in control theory, reinforcement learning, and embodied AI.

Qualifications

• 5+ years industry experience.
• Proven experience delivering production‑level robotic control systems in real‑world deployments (e.g., autonomous vehicles, manipulators, humanoid or mobile robots).
• Strong foundation in modern control techniques (e.g., MPC, adaptive control, system identification) and their integration with learning‑based methods.
• Deep understanding of reinforcement learning, imitation learning, and optimization for dynamic systems.
• Proficiency in Python and familiarity with C++ for real‑time robotics applications.
• Experience working with high‑fidelity simulators (e.g., Isaac Sim, Omniverse, Mujoco) for control development and testing.
• Excellent communication and teamwork skills, with the ability to bridge between AI research and robotic systems engineering.