Flight Dynamics Engineer (GNC) — Space Infrastructure | Austin, TX (On-site)

Client is a 12-person space infrastructure company building autonomous bio-factories in orbit — producing advanced materials and drugs impossible to make on Earth. Two satellites already launched, NASA TechLeap Prize winner, 8 more missions planned over the next two years. $30M funded, Series A incoming.

You'll own the navigation stack and control systems from scratch — the physicist of the team, ensuring every vehicle survives and performs through spaceflight.

What you'll do

• Design, develop, and validate GNC systems — attitude control, guidance logic, navigation estimation
• Build high-fidelity flight simulations, sensor models, and mission analysis tools
• Develop and maintain the full navigation and control software stack
• Be hands-on with physical vehicle testing and validation
• Serve as the team's physics expert across all mission conditions

Stack: Python, MATLAB, Simulink, C++, Julia

Strong fit if you have:

• 3–8 years GNC/flight dynamics engineering on real spaceflight or aerospace missions — must be able to describe specific technical contributions in detail
• Background at a new-space or defense program (SpaceX, Rocket Lab, Inversion, Stoke, Firefly, Raytheon hypersonics, missile defense)
• Proficiency in GNC algorithm development: attitude control, guidance logic, navigation estimation
• Simulation and modeling: flight sim, sensor modeling, Monte Carlo/dispersion analysis
• SIL/HIL environment development; C++ a plus
• BS or higher in Aerospace Engineering, Mechanical Engineering, Physics, or Controls

Details:

• Full-time, 5 days on-site in Austin TX (facility opening within 90 days; remote until then)
• $150K–$180K depending on experience + competitive equity
• Must be a U.S. Person (citizen or permanent resident); no visa sponsorship

Not a fit:

• Legacy aerospace prime backgrounds in non-ownership roles (Boeing program supporters, modelers with no subsystem ownership)
• Purely simulation/analysis experience with no hands-on vehicle testing or integration
• Candidates who need large team support structures or long modeling cycles to execute