Staff GNC Engineer (State Estimation)
Inversion
$161,000 - $221,000 / year
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Description
Turning Space into a Transportation Layer for Earth
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 vehicles do not fly through an empty sky. As the Staff GNC Engineer (State Estimation), you will give our vehicles an accurate, continuously updated picture of the world around them — estimating and predicting the state and behavior of friendly and non-cooperative systems external to the vehicle. This problem shares DNA with the prediction stacks that let autonomous cars anticipate the paths of surrounding vehicles and pedestrians, and you will draw on both classical estimation theory and modern learned methods to solve it in a far more demanding flight regime. In this role, you will:
- 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
- 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, Electrical Engineering, Robotics, a related field, or equivalent experience
- Experience with vehicle performance estimation and characterization from flight or test data
- Strong fundamental understanding of estimation theory, including Kalman filtering and its nonlinear variants, multi-hypothesis and interacting multiple model (IMM) approaches, and sensor fusion
- Experience deploying learned models to real-time, compute-restricted embedded environments
- Experience with trajectory optimization
- Experience with multi-target tracking, data association, and track management
- Familiarity with the flight dynamics of reentry, hypersonic, or orbital systems
- Experience developing 3-DOF and 6-DOF flight simulations
- Hardware-in-the-Loop (HITL) test experience
- Prior experience working in startups and/or small independent teams
Our office headquarters is located in Playa Vista, CA. This position requires in-office presence.
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.
About this role
Inversion is building spacecraft designed to deliver payloads anywhere on Earth in under an hour through extreme reentry conditions. As Staff GNC Engineer (State Estimation), you would own the perception and prediction layer that gives these vehicles accurate, real-time awareness of their environment — tracking both cooperative and non-cooperative objects observed through onboard sensors, predicting their behavior and intent, and feeding that intelligence to guidance and planning systems. The work blends classical estimation theory with modern deep learning, drawing parallels to autonomous vehicle prediction stacks but operating in a far more demanding flight regime.
You would develop state estimation and tracking algorithms, build neural network models for trajectory prediction, create probabilistic representations of external object state, and integrate these systems into 3-DOF and 6-DOF simulations and flight software. This requires strong fundamentals in estimation theory, dynamics, and sensor fusion, combined with hands-on experience training and deploying deep learning models in real-time environments. You'll work closely with guidance, sensors, and simulation teams to close vehicle-level performance gaps.
The role demands 9+ years developing and testing estimation, tracking, or GNC algorithms, with proven experience in behavior prediction for autonomous systems, modern deep learning frameworks, and programming in Python, MATLAB, or C++. You'll need to obtain a U.S. government security clearance and be based in-office at Inversion's Playa Vista headquarters. The salary range is $161,000–$221,000.
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Pay for this role
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