Role Overview:
We are seeking a GNC Engineer to play a critical leadership role in advancing Grid.aero’s flight control and guidance systems. In this position, you will own and evolve the Flight Controls architecture across the platform, driving technical excellence from design through flight test and operational deployment.
As a member of the engineering team, you will work closely with cross-functional partners including avionics, systems, and software to mature our technology. You will have significant influence over technical direction, processes, and long-term roadmap decisions.
This role offers the opportunity to apply deep GNC expertise to a mission-driven aerospace company that has moved beyond inception and is focused on execution, reliability, and growth. If you’re motivated by taking complex systems to the next level and shaping high-impact products at scale, we’d love to hear from you.
What You’ll Do:
- Develop modular and scalable flight control and decision-making algorithms and their simulation framework for Grid’s platform.
- Create control system modules in Simulink and/or C/C++ and help integrate them into the overall system.
- Evaluate stability and performance characteristics of control systems using simulation and flight test data, by using a CI/CD and automating analyses to the extent possible.
- Participate in test planning, execution and post-test analysis of aircraft
- Participate in cross-functional discussions about Grid’s product and mentor teams on software standards and best practices.
- Assist with the integration of computer vision, AI/ML for DAA and mission optimization, and AI-based pre/post-flight assessments.
Key Qualifications:
- 5+ years of experience in Guidance Navigation and Control algorithm development for fixed-wing aircraft
- Expertise with design, stability analysis, and simulation of PID and total energy-based control systems using MATLAB/Simulink
- Experience with flight testing of GNC algorithms and decision-making algorithms for DAA strongly preferred
- Familiarity with sensor calibration and noise characterization methods
- Familiarity with C/C++ and python
- Familiarity with adaptive control algorithms and data-driven control algorithms preferred.
