Staff GNC Engineer (Guidance)

Location: Playa Vista, California, United States

Department: Reentry

Who We Are: 

Inversion builds advanced reentry systems to deliver next-generation capabilities from space. 

Our mission is to make Earth radically more accessible by turning Low-Earth Orbit into an on-demand logistics domain. We see space not as a destination, but as a platform — one that unlocks unprecedented speed and global reach. 
  

Our spacecraft are designed to deliver payloads anywhere on Earth in under an hour, operating through extreme reentry conditions and landing with high precision. These systems open the door to new ways of testing, delivering, and operating at hypersonic speeds. 
  

Inherently dual-use, our technology is built to meet urgent national security needs while laying the groundwork for future commercial applications. Backed by leading investors including Y Combinator, Spark Capital, and Lockheed Martin Ventures, and working with partners such as the U.S. Space Force and NASA, Inversion is pushing the boundaries of what's possible in space-based defense and logistics. 
  

What You'll Do: 

Inversion's lifting-body reentry platform will be a highly maneuverable, highly accurate vehicle that is an industry first — and its guidance system is what makes that maneuverability count. As the Staff GNC Engineer (Guidance), you will be responsible for developing the guidance architecture for a high-performance maneuvering reentry vehicle, delivering high performance in the face of real-time mission updates. In this role, you will: 

• Own the guidance architecture for a maneuvering reentry vehicle from concept through flight 

• Develop guidance algorithms that replan trajectories onboard in response to real-time mission updates 

• Build and exercise 3-DOF and 6-DOF flight simulations to develop, stress, and validate guidance performance 

• Develop plant models of vehicle and subsystem dynamics to support algorithm design and simulation fidelity 

• Work with the broader GNC, simulation, and mission design teams to close vehicle-level performance 

• Mentor engineers across the GNC team 
    

Required Qualifications: 

• Bachelor's degree in Aerospace Engineering, a related field, or equivalent experience 

• Typically, 9+ years of applicable experience developing and testing guidance or GNC algorithms and systems 

• Experience with modern convex optimization methods for guidance (e.g., successive convexification / sequential convex programming, lossless convexification) 

• Experience developing and exercising 3-DOF and 6-DOF flight simulations 

• Strong fundamentals in flight mechanics, optimal control, and trajectory optimization 

• Proficiency in programming languages such as MATLAB, Python, or C++ for simulation and analysis 

• Demonstrated excellent verbal and written communication skills 

• Capable of working in a dynamic, fast-paced startup environment 

• This position is on-site at Inversion HQ in Playa Vista, CA. 

• Must have the ability to obtain and maintain a U.S. government Secret/Top Secret security clearance. 
    

Desired Qualifications: 

• Master's or PhD in Aerospace Engineering, a related field, or equivalent experience 

• Experience with real-time onboard optimization solvers (e.g., ECOS, CVXGEN, OSQP, or custom solvers) in compute-restricted environments 

• Experience with atmospheric entry guidance methods (e.g., numerical predictor-corrector approaches) 

• Experience building plant models of aerospace systems (aerodynamics, propulsion, actuators, sensors) 

• Experience with state estimation using limited data (Kalman filtering, sensor fusion) 

• Experience building guidance code deployed to real flight hardware 

• Hardware-in-the-Loop (HITL) test experience 

• Prior experience working in startups and/or small independent teams 

The California annual base salary for this role is currently $161,000-$221,000. Pay Grades are determined by role, level, location, and alignment with market data. Individual pay will be determined on a case-by-case basis and may vary based on the following considerations: interviews and an assessment of several factors that are unique to each candidate, job-related skills, relevant education and experience, certifications, abilities of the candidate and internal equity.