A complete application in a minute
Tailored resume and cover letter, ready to send.
AIM Intelligent Machines, Inc. in Seattle is seeking a Controls Engineer to develop and deploy control systems for autonomous heavy equipment. You will translate physics-based models into production code, validate behavior on test rigs, and collaborate with hardware, software, and field teams.
The role emphasizes hands-on work, from experiments and system identification to tuning controllers and ensuring safety, reliability, and performance across changing loads and terrains.
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.
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.
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.