Navigation Engineer, GNC

Furientis•Los Angeles, CA

3d•Onsite

About The Position

The GNC team writes the guidance algorithms, navigation solution, and autopilot that take a launched interceptor from rail to intercept under realistic noise, disturbances, and adversary behavior. On a modern missile, GNC decides whether the rest of the system's investment converts into a hit. We treat the navigation solution as the load-bearing wall every guidance and control decision rests on.

Requirements

B.S. in Aerospace, Electrical, Mechanical Engineering, Applied Math, Physics, or related.
7+ years of navigation or estimation work, with responsibility for one production navigation filter from architecture through flight test.
Designed and tuned an EKF (error-state or full-state) from first principles, not just consumed a vendor's nav solution.
Deep fluency with strapdown inertial navigation: quaternion and DCM mechanizations, coning and sculling, Earth and gravity models (WGS-84, J2+), and frame conventions (ECEF, ECI, NED, body).
Hands-on inertial sensor characterization: Allan variance, temperature calibration, g-sensitivity, scale factor and misalignment estimation, vibration rectification.
GNSS at receiver-output and signal-processing level: tight vs. loose coupling, RAIM, anti-jam and anti-spoof considerations, and realistic expectations under denial.
Flight-grade C/C++ (or Rust) for embedded targets.
Comfortable with fixed-step real-time execution, numerical conditioning of covariance matrices, and the difference between a prototype and a flight build.
Python (NumPy/SciPy) for modeling and Monte Carlo.
Able to stand up a harness with noise-source ablation and defend the results.
Bias for low-cost navigation: track record of meeting miss-distance requirements with MEMS IMUs where the legacy approach reached for a tactical-grade FOG or RLG.
Must be a U.S. Person.

Nice To Haves

M.S. or Ph.D. preferred.
You can defend your state vector, process noise, measurement model, and observability at the whiteboard.
Filter sophistication can buy back sensor grade.
AI-native working style: daily use of agentic coding tools (Claude Code, Codex, or similar) for filter scaffolding, Monte Carlo analysis, and report generation.
Direct flight experience on a tactical missile, munition, or interceptor navigation system.
High-g navigation experience (sustained launch loads, gun-launched munitions, or hard-impact events).
Transfer alignment from a moving host platform (air-launched or ship-launched).
GNSS-denied navigation: vision-aided, terrain-referenced, celestial, signals-of-opportunity, or magnetic-anomaly.
Production transition: moved a nav solution from prototype to volume manufacturing, including factory calibration flow.
Technical vendor relationships across the inertial and GNSS supply chain (tactical-grade IMUs, MEMS arrays, GNSS receivers, antennas).
Hobbyist drone or rocketry build and flight experience that translates to sensor packaging, vibration, and field-handling intuition.

Responsibilities

Design, tune, and harden an error-state EKF for tight INS/GNSS coupling, with graceful degradation under GNSS denial, jamming, and spoofing.
Characterize inertial sensors: bias, scale factor, misalignment, g-sensitivity, random walks, Allan variance, and temperature behavior across the envelope.
Own the navigation error budget across sensor noise, calibration residuals, lever arms, time sync, vibration rectification, and high-g transients.
Flow requirements down to suppliers and up to miss-distance.
Develop pre-launch alignment and in-flight alignment procedures (gyrocompass, transfer alignment, motion-based observability injection) suitable for tactical timelines.
Integrate aiding sensors as needed (GNSS, magnetometer, baro, vision, terrain-referenced, star tracker) and write the observability and fault-detection logic that decides when to trust them.
Build the full nav simulation stack: truth models, sensor error models, Earth and gravity models, Monte Carlo harness, and HWIL bench with real IMUs and GNSS receivers under motion.
Implement the navigation filter in flight-grade C/C++, with deterministic timing, fixed-step execution, and numerical conditioning suitable for a flight processor.
Plan and execute environmental qualification of the inertial assembly per MIL-STD-810 and program environments, with attention to vibration rectification and coning/sculling error.
Stand up the navigation HWIL from zero: rate table, three-axis motion simulator, GNSS RF simulator, and a bench that exercises the IMU filter against injected faults.