Physical AI Engineer, Lead

What you'll do

• Lead the architecture, development, and deployment of Physical AI systems for autonomous agents.
• Design and implement models for perception, planning, motion control, manipulation, navigation, and sensor fusion.
• Develop large-scale training pipelines using simulation, synthetic data, imitation learning, and reinforcement learning.
• Integrate multimodal AI including vision, language, and action models into physical platforms.
• Translate research innovations like robot learning and world models into production-ready solutions.
• Mentor senior engineers and establish engineering best practices and technical standards.
• Partner with stakeholders to define technical strategy and assess emerging technologies.

What we're looking for

• Doctorate degree in CS, Robotics, AI, EE, or ME (preferred).
• 8+ years of experience developing AI, robotics, autonomous systems, or machine learning solutions.
• Experience delivering production AI systems from concept through deployment.
• Experience with reinforcement learning, imitation learning, robot learning, computer vision, planning, autonomous navigation, manipulation, sensor fusion, multimodal AI, or foundation models.
• Experience with Python, C++, and modern AI frameworks such as PyTorch, JAX, TensorFlow, or Ray.
• Experience with robotic middleware and simulators such as ROS, ROS2, Isaac Sim, MuJoCo, or Gazebo.
• Ability to obtain a Secret clearance.
• Experience publishing research in robotics, embodied AI, or machine learning (preferred).
• Experience with robot foundation models, world modeling, and digital twins (preferred).
• Experience in humanoid robotics, dexterous manipulation, or mobile robotics (preferred).
• Experience with distributed training, GPU acceleration, and edge or embedded deployment (preferred).
• Experience contributing to open-source AI or robotics ecosystems (preferred).