Robotics Autonomy Engineer – Manipulation (Robotics)

Location: Irvine, California; on-site

Company

Develops risk-aware, field-ready embodied AI and autonomy systems for real-world robotic deployments.

What you will do

• Develop whole-body control and manipulation capabilities for humanoids and arm-equipped quadrupeds, coordinating base, torso, and arm motion.
• Turn field scenarios into repeatable hardware behaviors for interacting with environments, objects, and tools.
• Build model-based and learning-based manipulation policies, including policies trained from demonstrations and adapted vision-language-action models.
• Design grasping, contact, and force-control strategies that remain safe and reliable across varied objects, surfaces, lighting, and site conditions.
• Build simulation environments and evaluation pipelines, use field data for sim-to-real improvement, and validate behaviors on physical robots.
• Collaborate with locomotion, perception, and systems engineers to deliver end-to-end robotic capabilities.

Requirements

• Master’s degree or higher in Robotics, Computer Science, Engineering, or a related field; a PhD is strongly preferred.
• Deep expertise in robot manipulation or whole-body control, with hands-on experience developing and deploying behaviors on real robotic systems.
• Experience with robot arms, hands or grippers, humanoid or mobile manipulation platforms, kinematics, dynamics, contact modeling, and force control.
• Experience with manipulation planning and control, learning-based manipulation, perception integration, and simulation tools such as Isaac Lab, MuJoCo, or Drake.
• Strong Python and/or C++ skills in Linux-based development environments.
• Familiarity with PyTorch, JAX, or TensorFlow and a passion for building systems that operate in the physical world.

Nice to have

• Industry or startup robotics experience, including loco-manipulation, whole-body model predictive control, or deployment of vision-language-action models.
• Experience with teleoperation and demonstration-data pipelines, dexterous hands, tactile or force-torque sensing, or cross-embodiment manipulation policies.
• Experience deploying learning-based controllers with ONNX Runtime, NVIDIA TensorRT, or real-time onboard inference.
• Publications or open-source contributions in manipulation, whole-body control, or robot learning.
• Familiarity with ROS/ROS2, custom real-time-control middleware, or large-scale sim-to-real debugging.

Culture & Benefits

• Work with real robots, sensors, and hardware in lab testing and field deployments.
• Build systems intended for unstructured and previously unknown environments.
• Collaborate across AI, software, robotics engineering, product, field deployment, and technical communication.
• Join an inclusive workplace committed to merit-based evaluation and equal opportunity.