Robotics Autonomy Engineer - Locomotion

Samson Rose has been exclusively engaged by a pioneering Robotics & AI company in California to find a Robotics Locomotion Engineer. This is a high-impact opportunity to join a world-class team driving the development and deployment of cutting-edge reinforcement learning-based controllers for legged and humanoid robots. You’ll work at the intersection of advanced research, powerful simulation, and real-world field validation to push the limits of robotic mobility in unstructured environments.

A little about them:

• They are at the forefront of developing a groundbreaking, field-proven, hardware-agnostic brain technology that empowers a wide range of robots to operate autonomously in the most challenging environments—hazardous, off-road, and industrial settings—all without relying on GPS, maps, or pre-programmed routes.
• With over $100 million in funding from visionary leaders and institutions, they have the resources to rapidly turn their bold vision into reality and are making significant strides toward their ambitious goals.
• Their mission is to tackle one of the world’s most complex challenges: deploying robots in unstructured, previously unknown environments.
• By joining their team, you’ll have the chance to collaborate with some of the brightest minds in the industry. This world-class team thrives on creativity, resilience, and bold thinking. With a decade of success in the field, they've won DARPA challenge segments and brought together expertise from top-tier organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX.

The person they are looking for should have:

• Master’s degree or higher in Robotics, Computer Science, Engineering, or a related field (Ph.D. strongly preferred)
• Deep expertise in reinforcement learning, especially for continuous control tasks
• 2 years of experience developing and deploying locomotion policies for robotic systems
• Proficiency with simulation tools such as Isaac Gym, Isaac Lab, MuJoCo, or PyBullet
• Strong grasp of contact dynamics, control theory, and kinematics
• Experience working with legged and/or humanoid robots (e.g., quadrupeds, bipeds, or exoskeletons)
• Solid programming skills in Python and/or C in Linux environments
• Familiarity with ML frameworks like PyTorch or TensorFlow

Big pluses for:

• 3 years in an industry or startup robotics setting
• Experience deploying learned locomotion controllers on real-world robotic platforms
• Publications or open-source contributions in locomotion, reinforcement learning, or control
• Familiarity with ROS or custom middleware for real-time control
• Background in manipulation or whole-body coordination
• Experience debugging sim-to-real transfer at scale
• Contributions to RL libraries or simulation platforms
• Work on multi-agent learning or terrain-adaptive control systems
• Experience deploying neural network models on embedded robotic hardware

If this role is of interest to you, please apply with your current resume. We’ll follow up to schedule an initial call.