Staff GNC Engineer (State Estimation) Verified today

About Inversion

Inversion builds advanced reentry systems to deliver payloads anywhere on Earth in under an hour. The mission is to make Low-Earth Orbit an on-demand logistics domain by turning space into a transportation layer.

Our spacecraft operate through extreme reentry conditions and land with high precision. We work with the U.S. Space Force, NASA, and are backed by Y Combinator, Spark Capital, and Lockheed Martin Ventures.

What You'll Do

As Staff GNC Engineer (State Estimation), you will develop the estimation and prediction algorithms that give our vehicles an accurate, continuously updated picture of external systems. You will draw on classical estimation theory and modern learned methods to solve this problem in a demanding flight regime.

• Develop state estimation and tracking algorithms for aerospace systems external to the vehicle, spanning cooperative platforms and non-cooperative objects observed only through onboard sensor measurements
• Model and predict the behavior of external systems, including maneuvering objects with uncertain intent
• Train, validate, and deploy neural network models for trajectory and behavior prediction, and integrate them alongside classical filtering approaches
• Develop probabilistic representations of external-object state and intent that downstream guidance and planning functions can consume
• Build the metrics, tooling, and datasets needed to quantify estimation and prediction error and drive systematic improvement
• Integrate estimation and prediction algorithms into 3-DOF and 6-DOF simulation and carry them through real-time flight software
• Work closely with the guidance, sensors, and simulation teams to close vehicle-level performance

Required Qualifications

• Bachelor's degree in Aerospace Engineering, Electrical Engineering, Robotics, a related field, or equivalent experience
• Typically 9+ years of applicable experience developing and testing estimation, tracking, or GNC algorithms and systems
• Experience with behavior or trajectory prediction for autonomous vehicles, robotics, or similar multi-agent domains, including probabilistic prediction of agent intent
• Experience with modern deep learning frameworks (e.g., PyTorch, JAX) and the infrastructure to train models at scale
• Experience estimating and tracking the state of dynamic objects from noisy, intermittent, or limited sensor data
• Experience training and implementing neural networks for prediction, tracking, or related applications
• Solid grasp of classical mechanics, dynamics, and rigid body motion
• Proficiency in programming languages such as Python, MATLAB, or C++ for simulation and analysis
• Demonstrated excellent verbal and written communication skills
• Capable of working in a dynamic, fast-paced startup environment
• Must have the ability to obtain and maintain a U.S. government Secret/Top Secret security clearance

Work Location and Clearance

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