Principal Robotic Controls Engineer

About the role

WHO WE ARE

Aurelius Systems is a VC backed defense tech startup building autonomous, edge deployed directed energy systems for counter-UAS. We build laser weapons to shoot down drones.

We're a small team of engineers, former US military operators, and subject matter experts scaling America's directed energy dominance. The first cost effective, reliable and robust laser weapon system.

Our namesake isn't an accident. Marcus Aurelius wrote about doing the work in front of you, every day, without excuses. Henry Ford didn't wait for permission to reinvent manufacturing. That's how we operate: small team, unreasonable output, no hiding behind the unachievable.

In addition to our San Francisco lab, we opened a Detroit manufacturing hub and field test weekly on our own 400-acre private range.

THE ROLE & YOUR IMPACT

We need a Principal Controls Engineer who owns the math behind putting a laser on a drone and keeping it there.

You'll own beam control and tracking as a theory domain across the whole system: the nested coarse and fine pointing architecture, the estimators that fuse radar cues, EO/IR track and inertial data, the jitter and latency budgets, and the analysis that says what the system can and cannot hit before we drive to the range to find out. You'll partner with the perception, optics and mechanical leads on architecture and roadmap, and you'll be the senior technical voice on controls decisions inside the company.

You'll derive the loop, run it in our in-house simulator, and have it on the hardware in days, not weeks. Then you'll stand on our outdoor range, control and refine laser positioning yourself, and watch it hold microradian precision on a maneuvering drone.

WHAT YOU'LL OWN

- Control architecture for the beam director: coarse gimbal and fine steering mirror loop structure, bandwidth allocation, multi-rate design, and the handoff between stages

- Target state estimation: Kalman, IMM and nonlinear filters that fuse radar cue, EO/IR track and inertial data into a predicted aimpoint, with latency compensation designed in, not patched on

- Line-of-sight stabilization and jitter rejection: inertial stabilization, accelerometer feedforward, notch and adaptive filtering for structural modes, and the control-structure interaction analysis behind them

- The pointing error budget and the field result: jitter, bias, latency and atmospheric terms allocated across the system, then microradian pointing precision achieved and held on our outdoor range against dynamic, real-world targets through hands-on experimentation and deployment

- Plant modeling and system identification: frequency-domain and time-domain ID of gimbal, mirror and structure, hardware-in-the-loop validation, and the models our in-house simulators run on

- Robustness and stability analysis: margins, sensitivity, worst-case disturbance and parameter variation, with the proof, not just the Bode plot