Robotics Control Engineer – Real‑Time Model Predictive Control

About the role

We are seeking a Robotics Control Engineer to lead the development of advanced real‑time control algorithms for autonomous robots. You will work closely with the Head of Robot Engineering to shape the core navigation and perception capabilities of our fleet.

Key responsibilities

• Define and quantify control requirements for path tracking, including accuracy and disturbance rejection.
• Design, implement, and validate Model‑Predictive Control (preferably Nonlinear MPC) solutions that run in real‑time on robot hardware.
• Develop state‑estimation and sensor‑fusion pipelines, creating observation and prediction models for robust localization in dynamic outdoor environments.
• Implement Extended Kalman Filters to fuse GNSS, IMU and other sensor data, handling non‑linear vehicle dynamics.
• Produce original intellectual property, focusing on the dynamics and constraints of non‑holonomic vehicles.

Required profile

• PhD or engineering degree in Robotics, Automation or a related field.
• Minimum 3 years of experience in dynamic systems modeling and control‑law synthesis.
• Proven track record of deploying Nonlinear MPC on physical robots, not just in simulation.
• Fluent English and ability to bridge scientific rigor with industrial deployment.

Required skills

• Model‑Predictive Control (MPC), especially Nonlinear MPC.
• Extended Kalman Filter (EKF) and sensor‑fusion techniques.
• Strong C++ programming skills.
• Experience with ROS (Robot Operating System).
• Knowledge of GNSS, IMU integration; SLAM is a plus.

What we offer

• Opportunity to create core navigation algorithms for cutting‑edge robots.
• Collaborative research‑to‑industry environment.
• Competitive compensation and benefits package.