About Job:
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 Include:
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
Skills / Competencies Required:
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.