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.