GNC Algorithm Engineer

About the Role

We are looking for a GNC Algorithm Engineer to join our team and contribute to the development and implementation of Guidance, Navigation, and Control (GNC) solutions for unmanned aerial vehicles (UAVs).

In this role, you will participate in the full algorithm development lifecycle - from mathematical modeling and simulation to implementation, optimization, and real-world flight testing.

Key Responsibilities

• Develop, test, and optimize Guidance, Navigation, and Control (GNC) algorithms for UAVs
• Modify and adapt algorithm parameters for specific aircraft platforms
• Build dynamic models and perform simulations (SITL/HITL) using tools such as MATLAB/Simulink, JSBSim, Gazebo, or similar environments
• Support, configure, and tune autopilot systems such as ArduPilot and PX4
• Integrate and process data from onboard sensors (IMU, GPS/GNSS, barometer, magnetometer)
• Implement and tune control algorithms, including PID, LQR, nonlinear, and adaptive controllers
• Analyze flight data and telemetry to improve algorithm performance and system reliability
• Participate in laboratory and field testing of developed solutions
• Collaborate closely with cross-functional engineering teams throughout the development process

Requirements

• Higher technical education in Aerospace Engineering, Mechatronics, Robotics, Mathematics, Cybernetics, or a related field
• Proven experience developing GNC algorithms for UAVs, autonomous systems, or robotic platforms
• Strong programming skills in C++, Python, and/or MATLAB, with focus on numerical methods and algorithm efficiency
• Hands-on experience with modeling and simulation tools such as MATLAB/Simulink, JSBSim, Gazebo, AirSim, or similar (SIL/HIL environments)
• Experience with ArduPilot or PX4, including configuration, tuning, and integration with control algorithms
• Strong understanding of sensor integration and data processing (IMU, GPS/GNSS, barometer, magnetometer)
• Practical experience implementing and tuning control methods (PID, LQR, nonlinear or adaptive controllers) under real hardware constraints

Nice to Have

• Experience applying Machine Learning / AI approaches for optimization or adaptation of GNC algorithms
• Experience with ROS in robotics or aviation projects
• Participation in research initiatives, hackathons, conferences, or publications related to control and navigation
• Practical multicopter piloting experience