Controls Engineer, Whole-Body Control

The Mission

GRAM is a self-replication company creating machine labor for the physical economy.

Our first research frontier is self-preservation: the base case of physical self-replication. We are building a new class of machines called insectoids that can survive, coordinate, and recover without humans. We believe scalable machine labor requires more than single-agent task generality or machines shaped in our image.

About the role

You will build the real-time control architecture that coordinates an insectoid's full body across changing geometry, orientation, contact, load, and machine state. The work spans dynamics, contact constraints, force allocation, trajectory tracking, actuator limits, transitions, disturbance rejection, and recovery, carried through production C++ and onto hardware.

You will develop the control-oriented models, system-identification methods, and hardware-in-the-loop environments needed to build and validate the controller, then establish its measured operating envelope on the physical machine.

What you will do

• Design whole-body controllers that coordinate motion and contact forces across coupled degrees of freedom.

• Implement real-time control software in C++ with explicit timing, numerical stability, saturation, and fault behavior.

• Develop control-oriented dynamics models, system-identification experiments, and actuator characterizations that improve controller fidelity.

• Integrate state estimation, trajectory generation, manipulation, embedded systems, and safety logic into one testable control path.

• Define quantitative envelopes for tracking error, contact stability, disturbance rejection, transition success, compute latency, and recovery.

• Build controller simulations, hardware-in-the-loop tests, and physical-machine tests that reproduce failures and prevent regressions.

• Use test evidence to distinguish controller defects from estimation error, unmodeled dynamics, actuator limits, and mechanical faults.

• Document model validity and confirm simulated results on physical hardware.

Minimum qualifications

• Bachelor's degree in mechanical engineering, electrical engineering, robotics, controls, applied mathematics, or a related field, or equivalent practical experience.

• Demonstrated experience developing feedback control for a multi-degree-of-freedom robot, vehicle, aerospace platform, or other nonlinear physical system.

• Strong C++ and Python skills and command of rigid-body dynamics, linear systems, optimization, and numerical methods.

• Hands-on experience with a controls or dynamics stack such as Drake, Pinocchio, MuJoCo, ROS 2 control, Eigen, or an equivalent internal framework.

• Deployed a controller on physical hardware and can present measured tracking, stability, latency, or disturbance-rejection results plus a failure that required redesign.

Preferred experience

• Whole-body control, model predictive control, inverse dynamics, contact optimization, or legged robotics.

• Real-time Linux, deterministic communications, actuator torque control, or safety-rated motion systems.

• Controls deployed in aerospace, autonomous vehicles, industrial robotics, or field robotics.

Compensation

The annual base salary range for this El Segundo position is $190,000–$230,000. An offer within this range will reflect the position's approved scope and the candidate's demonstrated role-relevant skills and experience.

Working at GRAM

This role is based on-site in El Segundo and is inseparable from hardware. You will instrument machines, run tests, and make control decisions from physical data throughout the development cycle.

Interview Process

After submitting your application, we review your portfolio and any exceptional work you've shipped. If your application demonstrates the caliber we seek, you'll enter our interview process, which is designed for speed and substance. We aim to complete it within one week from start to finish.

Trust in the Process

GRAM expects deep trust and ownership from its people, and we begin by extending the same to candidates. We treat your information, prior work, and conversations with discretion.