Senior Embodied AI Engineer - Controls

AIM Intelligent Machines; Seattle (WA); On-site; USD 100,000 - 130,000; Full time

Job summary

AIM Intelligent Machines in Seattle is looking for a skilled robotics engineer to automate, develop, and validate advanced control systems for robotic applications. The role demands collaboration with engineers to integrate AI control stacks and conduct vital experiments.

The ideal candidate has over 5 years of experience delivering production-level robotic systems and a strong foundation in control techniques and reinforcement learning. Proficiency in Python and familiarity with C++ are required.

Qualifications

• 5+ years industry experience.
• Proven experience delivering production-level robotic control systems.
• Strong foundation in modern control techniques.

Responsibilities

• Automate, develop, implement, and validate advanced control algorithms.
• Design and conduct experiments to enhance control robustness.
• Collaborate with engineers to integrate AI control stacks.

Skills

Robotic control systems

Reinforcement learning

Python

C++

Control theory

Tools

Isaac Sim

Omniverse

Mujoco

Job description

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.