Navigation Engineer, GNC

America is critically deficient in production of defensive munitions- we currently produce shipborne interceptors in the few hundreds per year while our adversaries are producing offensive threats in the tens of thousands per year. Furientis was started to help solve this problem- introducing a new class of cost-effective, high production rate, interceptor missiles. We're seeking motivated individuals who internalize this problem and are eager to apply their past experience in similar industries (aerospace, defense, automotive/racing, robotics) and out of the box thinking to solve this problem for the US and its allies.About The TeamThe 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.What You'll DoDesign, tune, and harden an error-state EKF for tight INS/GNSS coupling, with graceful degradation under GNSS denial, jamming, and spoofingCharacterize inertial sensors: bias, scale factor, misalignment, g-sensitivity, random walks, Allan variance, and temperature behavior across the envelopeOwn 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-distanceDevelop pre-launch alignment and in-flight alignment procedures (gyrocompass, transfer alignment, motion-based observability injection) suitable for tactical timelinesIntegrate 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 themBuild 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 motionImplement the navigation filter in flight-grade C/C++, with deterministic timing, fixed-step execution, and numerical conditioning suitable for a flight processorPlan and execute environmental qualification of the inertial assembly per MIL-STD-810 and program environments, with attention to vibration rectification and coning/sculling errorStand 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 faultsSkills We're Hiring ForB.S. in Aerospace, Electrical, Mechanical Engineering, Applied Math, Physics, or related. M.S. or Ph.D. preferred7+ years of navigation or estimation work, with responsibility for one production navigation filter from architecture through flight testDesigned and tuned an EKF (error-state or full-state) from first principles, not just consumed a vendor's nav solution. You can defend your state vector, process noise, measurement model, and observability at the whiteboardDeep 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 rectificationGNSS at receiver-output and signal-processing level: tight vs. loose coupling, RAIM, anti-jam and anti-spoof considerations, and realistic expectations under denialFlight-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 buildPython (NumPy/SciPy) for modeling and Monte Carlo. Able to stand up a harness with noise-source ablation and defend the resultsBias 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. Filter sophistication can buy back sensor gradeAI-native working style: daily use of agentic coding tools (Claude Code, Codex, or similar) for filter scaffolding, Monte Carlo analysis, and report generationBonus Points ForDirect flight experience on a tactical missile, munition, or interceptor navigation systemHigh-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-anomalyProduction transition: moved a nav solution from prototype to volume manufacturing, including factory calibration flowTechnical 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 intuitionEligibility & Logistics Location: On-site at our Los Angeles, CA HQ; remote work is not available. Monthly weekend travel for test events and supplier engagements. Clearance: A clearance is not required for this position. Must be a U.S. Person.Equal Opportunity & Export Compliance Furientis is an equal-opportunity employer. To comply with U.S. export control laws, employment is contingent on eligibility to access export-controlled information.We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.