GNC Simulation & Validation Engineer
About the Role
We are seeking a GNC Simulation & Validation Engineer to design, validate, and refine high-fidelity simulation systems focused on flight dynamics, control systems, and state estimation for UAVs and autonomous robotic platforms. You will work at the intersection of dynamics, control, and real-world validation, ensuring that simulation accurately reflects real system behavior and that GNC algorithms perform reliably before deployment. This role is critical to flight safety, performance, and sim-to-real alignment.
Key Responsibilities
- Develop and maintain nonlinear 6-DOF dynamics models including aerodynamics, propulsion, and disturbances
- Model and validate actuators, control allocation, and vehicle response characteristics
- Build and maintain simulation environments across SITL/HITL frameworks and platforms (Gazebo, Isaac Sim etc) integrated with ArduPilot/PX4 for closed-loop autonomy validation
- Analyse flight logs to debug controller, estimator, and system-level performance
- Perform system identification and parameter estimation to align simulation models with real-world behavior
- Validate and tune control systems and state estimation pipelines (EKF-based sensor fusion)
- Collaborate with autonomy and firmware teams to ensure control and estimation robustness prior to deployment
Required Skills & Experience
- Strong fundamentals in rigid body dynamics, nonlinear system modeling, and flight mechanics, including static and dynamic stability of UAVs and its implications for control design and vehicle response
- Good understanding of coordinate frames, transformations, and attitude representations (Euler angles, quaternions)
- Solid understanding of control systems and state estimation (EKF, sensor fusion)
- Proven experience validating system behavior in simulation environments (e.g., Gazebo, NVIDIA Isaac Sim), including closed-loop testing under disturbances/failures and alignment with real-world flight data or logs
- Experience with ArduPilot or PX4 SITL/HITL workflows
- Proficiency in C++ and Python
Preferred Experience
- Experience with system identification and parameter estimation from real UAV flight data to derive and validate dynamic models
- Experience in frequency-domain analysis, stability characterization, and systematic controller tuning for UAV platforms
- Exposure to hardware-in-the-loop (HIL) testing with real sensors and flight controllers
- Familiarity with ROS2-based systems for integration with autonomy stacks
- Prior work on UAVs or aerial robotics platforms
Education & Experience
Bachelor's or Master's degree in Aerospace, Robotics, Mechanical Engineering, or related field, with 2–6 years of experience in GNC, flight dynamics, or simulation-driven validation.
