Controls Engineer

Zeromatter Technologies Inc; Mountain View (CA); On-site; USD 120,000 - 190,000; Full time

Job summary

Zeromatter Technologies Inc. in Mountain View, CA is seeking a Controls Engineer for our Dynamics team. You will build control systems for simulation of vehicles, drones, planes, and robots, translating user intent into controllable trajectories and behaviors.

Responsibilities span developing controllers, trajectory generation, and validating models with real-world data. Proficiency in Rust/C++/Python is required; aerospace/robotics background is a plus.

Qualifications

• Engineering degree in aerospace, mechanical, electrical engineering, robotics, physics, or equivalent experience.
• Experience developing control systems and/or dynamics models for automotive, aerospace, drone, or robotics applications.
• Strong knowledge of controller architectures (PID, LQR, MPC).
• Experience with trajectory generation and optimization.
• Strong foundation in physics and dynamics; able to derive and implement equations of motion for new vehicle/robot classes.
• Experience using simulation in control development and validation workflows.
• Proficiency in Rust, C++, and/or Python.
• Bonus: experience with vehicle dynamics or multibody dynamics simulation; flight dynamics or drone control systems; sim-to-real transfer; machine learning familiarity.

Responsibilities

• Develop controllers for vehicle classes within our simulator (e.g. fixed-wing aircraft, drones, ground vehicles).
• Design trajectory generation systems translating user intent into flyable paths paired with controllers.
• Characterize and replicate control systems to match real-world behavior in simulation.
• Build trajectory generation and mid-level control layers enabling policy interaction with simulated robots.
• Implement controller architectures (PID, LQR, MPC) suited to each vehicle class.
• Validate models and controllers against real-world data and physical intuition.
• Create reusable libraries and tooling in Rust, C++, and/or Python to scale development.

Skills

Rust

C++

Python

Education

Engineering degree or equivalent experience

Job description

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