Job Title

Role Overview The ideal Robotics & Mechatronics Engineer at Precision AI is someone who can model, simulate, and tune dynamic systems, and thenvalidatethem in the real world.Youllwork in a multidisciplinary environment alongside embedded, mechanical, GNC (Guidance, Navigation, and Control), and software engineers, developing control strategies that directlyimpactUAV stability, safety, and spray performance from concept through flight testing. Ifyoureexcited to dive deep into system dynamics without ego, and you enjoy turning theory into working, stable behavior on a real platform, this role will feel like home. You bring strong fundamentals in control theory, comfort with modeling and stability analysis, and the grit to iterate through tests until the system converges. Youllspend your days building models, designing PID control loops, running simulations, and analyzing stability (including frequency-domain methods like Bode plots) to improve platform behavior. Some daysyoullbe tuning in simulation; other daysyoullbe in the field, adjusting parameters andvalidatingperformance under agricultural shock and vibration. At Precision AI, we move fast and build things that matter. If you want to own one of the highest-leverage technical risks on the program and help deliver reliable autonomy in real farm conditions,wedlove to meet you. This role is hybrid in Calgary due to the hands-on nature of testing, integration, and UAV flight verification and validation. Key Responsibilities Control System Design & Tuning Design and tune PID control loops for stability, responsiveness, and robustness across flight conditions. Define controlobjectivesand performance metrics tied to safety and spray accuracy. Develop control logic that accounts for real-world disturbances, saturation, delays, and sensor noise. Support integration of control algorithms into embedded implementations in partnership with firmware teams. Modeling, Dynamics & Stability Analysis Build dynamic models of the platform and subsystems (actuators, sensors, airframe responses) to inform control design. Perform stability analysis using frequency-domain techniques (e.g., Bode plots) and converge on stable operating regions. Develop andvalidatesensor/estimation assumptions (rate limits, latency, noise characteristics, update timing). Use MATLAB or another scripting language to prototype and evaluate control loops and tuning approaches. Document modeling assumptions, control architectures, and tuning rationale for repeatable engineering decisions. Simulation, Testing & Iteration Build and run simulations (including dynamic simulation) tovalidatecontrol strategies before field deployment. Design test plans for tuning and validation, including step responses, frequency sweeps, and disturbance testing. Support field testing and iterative tuning under agricultural environments (shock, vibration, wind, dust). Analyze test data toidentifyinstabilities, coupling effects, and performance bottlenecks; implement improvements quickly. Cross-Functional Collaboration Work closely with Embedded Engineers to ensure real-time constraints, sensor timing, and implementation details match control intent. Collaborate with Mechanical and Electrical teams to align actuator/sensor selections and physical constraints with stability needs. Relevant Experience 36 years ofcontrolsengineering experience withdemonstratedownership of modeling and tuning work. Strong foundationin system dynamics, control theory, and stability analysis (time and frequency domain). Experience with MATLAB (or equivalent) for control prototyping, simulation, and analysis. Experience modeling dynamic systems and translating models into practical control implementations(i.e.System ID or similarhardwarecharacterization techniques) Background inagtech, automotive, aerospace, robotics, or other vibration/shock-heavy platforms. What You Bring Excitement to dive deep:yourecurious, rigorous, and motivated to converge on stable real-world behavior. Low-ego collaboration style: you partner well across disciplines and focus on outcomes over credit. Ability to translate math and theory into practical engineering decisions and repeatable tuning processes. Strong communicationskills for cross-functional collaboration. Willingness to travel 5-10% for field deployments and integration tests Bonus Experience tuning controls on real vehicles (UAVs, automotive, aerospace, agricultural equipment). Experience with state estimation / sensor fusion concepts (even if not your primary ownership). Experience with real-time implementation constraints and embedded integration workflows. Comfort analyzing large test datasets and building repeatable analysis scripts. Experience working on safety-critical or high-reliability systems. Competition orOpen SourceTeam Experience #J-18808-Ljbffr