Robotics Controls Engineer Lead

About the company GRAM Corporation scales skilled labor for the physical economy. We design, manufacture and operate insectoids, general-purpose machines not built in our image. They work in large populations on the critical infrastructure nations depend on. The electric grid comes first. Our research is in how those populations coordinate and keep themselves running. The goal is Self-Replication (SR), the point where a population of machines delivers more labor than it takes to build and run. The role You will own locomotion controls for GRAM’s multi-legged robot, from the low-level actuator loops to whole-body control on uneven terrain. Model-based control is the priority, and learning-based control experience is a bonus. This is a hands-on role: you will write the controllers yourself, tune and prove them on the robot, and work closely with the Autonomy, Simulation and Systems Integration teams. You start as an individual contributor, with a path to build and lead a controls team as the company grows Responsibilities: - Develop and implement model-based locomotion control systems for multi-legged robots. - Write and optimize low-level actuator loops and whole-body control algorithms. - Test and validate control systems on physical robots in various terrains. - Collaborate with Autonomy, Simulation, and Systems Integration teams for seamless integration. - Contribute to the research and development of innovative control strategies. - Provide technical leadership and mentorship as the team expands. Required Skills: - Bachelor's or Master's degree in Robotics, Electrical Engineering, Computer Science, or a related field. - Strong expertise in model-based control systems for robotic platforms. - Experience with low-level actuator loop development and optimization. - Proficiency in programming languages such as C++ and Python. - Knowledge of learning-based control methods is a plus. - Excellent problem-solving skills and attention to detail. - Strong teamwork and communication skills. What you will do: - Own locomotion and whole-body control for the multi legged robot on uneven terrain, and the body state estimation from IMU, joints and contact that it runs on. - Own low level actuator control and system identification of actuators and contact. - Set measurable targets for tracking, stability, disturbance rejection and latency, and prove them on hardware. - Tune, debug and validate controllers on the robot, working with the Autonomy, Simulation and Systems Integration teams. What you bring: - Model predictive control or whole-body optimization-based control, deployed on physical hardware with measured results. - Solid grounding in rigid body dynamics, forces, contact stability and latency. - Strong C++ and Python. - Experience with state estimation for legged or floating base robots. - 8+ years of hands-on controls work on physical robots. A PhD in controls or robotics lowers the experience bar Nice to have: - Legged robot experience strongly preferred. - Experience integrating learned policies with a model-based controller - Trajectory optimization and reduced order models for legged locomotion. - Torque controlled or quasi direct drive actuators. - Footstep planning and integration with terrain perception. - Tuning hardware and controllers for repeated impact loading. - Tools such as Drake, Pinocchio or MuJoCo. Why join - A clean slate: define how a new multi-legged robot moves. - Early equity, included in the package - The chance to own a domain and build a team around it as the company scales. - A hands-on culture where engineers work directly on the core technology.