Hiring: Staff GNC Engineer (State Estimation) Company: Inversion Location: Los Angeles, CA Job Posted Time: 2026-09-10 13:33:37 Employment Type: On-site Target Skills & Keywords : Aerospace Engineering, C++, Deep Learning, Embedded Systems, MATLAB, PyTorch, Python, Security Clearance, Spark About the job Experience: •9+ years of applicable experience developing and testing estimation, tracking, or GNC algorithms and systems Required Skills: •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 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 •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 •This position is on-site at Inversion HQ in Playa Vista, CA. •Master's or PhD in Aerospace Engineering, Electrical Engineering, Robotics, a related field, or equivalent experience •Strong fundamental understanding of estimation theory, including Kalman filtering and its nonlinear variants, multi-hypothesis and interacting multiple model (IMM) approaches, and sensor fusion Compensation: •$161,000 - $221,000 / year Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!