Principal Controls Engineer

About us

AIM builds autonomy for the real world—robots that move mountains. Our systems bring together software, hardware, and robotics to turn heavy equipment into intelligent machines that reshape how earthmoving is done.
Controls connect our autonomy software to the physical machine. Our machines need to move precisely and predictably while digging soil, moving rock, and working across changing terrain. That means dealing with varying loads, nonlinear actuator behavior, uncertain ground conditions, and the realities of operating heavy equipment on active jobsites.
We're looking for a Controls Engineer to develop the control systems that make these machines capable, reliable, and safe.
About you

You enjoy taking a controls problem from understanding the physics through implementation, testing, and deployment. You're comfortable developing models, writing production software, and working directly with hardware to understand why a machine behaves the way it does.
You have strong control fundamentals and practical experience making physical systems perform reliably. You use experiments and data to challenge assumptions, diagnose problems, and improve performance.
You take ownership of results and work well across software, electrical, mechanical, and field teams. You're curious about heavy machinery and eager to learn its dynamics.
About us together

We will build control systems that turn autonomous plans into precise, coordinated machine motion. Our work will span simulation, test equipment, and deployed machines, with field results guiding each improvement.
You'll help solve problems where control theory meets changing loads, actuator limits, sensor noise, and contact with the ground. You'll see your work move real machines and directly improve how they operate.
What you will own

Develop machine control algorithms

Design, implement, and tune feedback and feedforward controllers for machine motion and implement control.

Translate motion targets into coordinated actuator commands that account for machine dynamics and operating limits.

Improve tracking accuracy, responsiveness, stability, and repeatability across operating conditions.

Characterize machine dynamics

Design and run experiments to understand actuator response, delays, friction, deadbands, and load-dependent behavior.

Develop models and system identification methods that support controller design and tuning.

Build calibration and tuning procedures that can be repeated across machines.

Deliver production controls software

Implement reliable control software with clear interfaces, diagnostics, and automated tests.

Collaborate with planning, state estimation, embedded, and hardware teams to integrate controllers into the autonomy system.

Work with systems and safety engineers to define and validate command limits, fault responses, and transitions between operating modes.

Validate performance on real machines

Develop tests that progress from simulation and bench testing to controlled machine trials.

Analyze telemetry and field logs to identify root causes and verify improvements.

Establish measurable performance criteria and regression tests.

Work directly with field engineers and operators to troubleshoot issues and improve deployed machine behavior.

Qualifications

Bachelor's or Master's degree in Mechanical Engineering, Electrical Engineering, Robotics, Aerospace Engineering, or a related field, or equivalent practical experience.

Experience designing, implementing, and tuning controllers on physical systems.

Strong foundation in feedback control, dynamic systems, stability, and discrete-time implementation.

Practical experience with modeling, system identification, and experimental validation.

Proficiency in C++ and experience with Python or MATLAB for analysis and development.

Ability to diagnose problems across software, sensors, actuators, and mechanical systems.

Clear communication, strong ownership, and a willingness to work hands-on with machines.

Preferred qualifications

Experience with heavy equipment, off-road vehicles, mobile robotics, or other systems operating under variable loads.

Familiarity with model predictive control, optimal control, nonlinear control, or adaptive control.

Experience with real-time or embedded control software and machine communication interfaces such as CAN.

Experience with hydraulic or electrohydraulic systems, including valves, pumps, cylinders, or hydraulic actuator control.

Experience with simulation, hardware-in-the-loop testing, or automated controller calibration.

Experience developing fault detection and safe operating behavior for physical systems.

J-18808-Ljbffr