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 themCharacterize 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 ourselvesBuild 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 commandsImplement controller architectures (PID, LQR, MPC, and other optimal control approaches) suited to each vehicle or robot classValidate models and controllers against real-world data and physical intuition to ensure simulated behavior is physically accurateBuild reusable libraries and tooling (in Rust, C++, and/or Python) to support this work at scaleQualificationsYou have an engineering degree in a related field (e.g. aerospace, mechanical, electrical engineering, robotics, physics) or equivalent working experienceDemonstrated experience developing control systems and/or dynamics models for automotive, aerospace, drone, or robotics applicationsStrong knowledge of controller architectures, such as PID, optimal control, LQR, and MPCExperience with trajectory generation and optimizationStrong foundation in physics and dynamics, comfortable deriving and implementing equations of motion for new vehicle or robot classesExperience using simulation as part of a controls or model development and validation workflowProficient in Rust, C++, and/or PythonBonus: Experience with vehicle dynamics or multibody dynamics simulationBonus: Experience with flight dynamics, aircraft modeling, or drone control systemsBonus: Experience characterizing or reverse-engineering existing control systemsBonus: Experience with sim-to-real transfer of control policies onto physical hardwareBonus: Familiarity with machine learning frameworks, training, and inference is preferable given close collaboration with the team’s more robotics/ML-focused engineers