Controls Engineer

As a Controls Engineer on our Dynamics team, you'll build the control systems that let every actor in our simulation platform behave correctly, from vehicles driving around urban/suburban/highway environments, to an airliner taxiing, to a runway and performing a take off, to a drone flying a path between two points, to a robot executing a trajectory handed to it by a policy. Responsibilities may vary from month to month, but here are some examples of things you might find yourself working on:

• Develop controllers for vehicle classes not yet supported in our simulator (e.g. fixed-wing aircraft, articulated construction equipment, etc.)

• Design trajectory generation systems that translate high-level user intent (e.g. start/end points, altitude, flight parameters) into flyable paths for aircraft and drones, paired with controllers that can track them

• Characterize and replicate the control systems of robots we've purchased so their real-world behavior is faithfully reproduced in simulation, and contribute to controllers we develop ourselves

• Build the trajectory generation and mid-level control layers that let robotics policies interact with simulated robots through trajectories and actions rather than low-level torque commands

• Implement controller architectures (PID, LQR, MPC, and other optimal control approaches) suited to each vehicle or robot class

• Validate models and controllers against real-world data and physical intuition to ensure simulated behavior is physically accurate

• Build reusable libraries and tooling (in Rust, C++, and/or Python) to support this work at scale

Qualifications

• You have an engineering degree in a related field (e.g. aerospace, mechanical, electrical engineering, robotics, physics) or equivalent working experience

• Demonstrated experience developing control systems and/or dynamics models for automotive, aerospace, drone, or robotics applications

• Strong knowledge of controller architectures, such as PID, optimal control, LQR, and MPC

• Experience with trajectory generation and optimization

• Strong foundation in physics and dynamics, comfortable deriving and implementing equations of motion for new vehicle or robot classes

• Experience using simulation as part of a controls or model development and validation workflow

• Proficient in Rust, C++, and/or Python

  • Bonus: Experience with vehicle dynamics or multibody dynamics simulation

  • Bonus: Experience with flight dynamics, aircraft modeling, or drone control systems

  • Bonus: Experience characterizing or reverse-engineering existing control systems

  • Bonus: Experience with sim-to-real transfer of control policies onto physical hardware

  • Bonus: Familiarity with machine learning frameworks, training, and inference is preferable given close collaboration with the team's more robotics/ML-focused engineers