State Estimation and Navigation Engineer

About the role

This role is designed for an experienced state estimation specialist who will eventually own the navigation and estimation problem end-to-end for our interceptor systems.

This is a deep individual-contributor role. You will work alongside our GNC and autonomy leads to shape, architect, and independently execute the state estimation solutions that deliver mission-critical capability.

Navigation in our domain is unforgiving. Our vehicles are low-SWaP and operate in GPS-contested environments, across high-dynamic flight regimes, against maneuvering targets, with hard real-time constraints and little margin for a bad estimate.

We are looking for someone who treats this as the central challenge it is, and who has the depth to drive a solution from first-principles observability analysis through flight-proven, embedded implementation.

We are looking for evidence-driven engineers: individuals who prioritize physical reality over opinion and have the technical conviction to derive the best solution as supported by data. In this role, that means bringing the judgment to know which estimator architecture the problem actually demands, the rigor to prove it against flight data, and the autonomy to test, troubleshoot, validate in flight, and deliver an effective solution.

What you'll do

You will lead the design and implementation of the navigation and estimation stack, from first-principles observability analysis through flight-proven embedded execution. You will work in close partnership with the guidance and controls teams, but the architecture, rigor, and validation of the estimation solution are yours to drive.

You will focus on problems in all of the following areas:

• Estimator Architecture & Design: Select and justify the estimator architecture the problem actually demands, including KF variants, factor graphs, and related approaches, grounded in observability analysis of the vehicle dynamics and sensor suite rather than defaulting to a familiar filter.
• State-Driven Guidance & Control Co-Design: Work across the estimation-G&C boundary to align the available state with the guidance and control laws the intercept requires, recognizing that estimator capability and achievable guidance are mutually constraining.
• GPS-Contested & Denied Navigation: Develop navigation solutions that hold up as GNSS degrades or disappears, maintaining a trustworthy state through the regimes where a bad estimate ends the mission.
• Multimodal Sensor Fusion: Fuse heterogeneous sensing, including inertial, GNSS, vision, and seeker/target sensors, into a coherent, real-time state under low-SWaP constraints.
• Robustness to Latency & Degradation: Handle delayed and asynchronous measurements, detect and ride through sensor degradation or outright failure, and inform the case for redundant or complementary sensing where the estimate demands it.
• Target-Relative Navigation: Estimate the relative state of maneuvering targets with the fidelity and latency the intercept demands.
• Sensor Selection & Integration: Partner with the hardware and electrical design teams to drive sensor selection, placement, and integration, closing the loop between what the estimator needs and what the vehicle carries.
• Flight Validation: Prove estimators against truth data across SITL/HITL and real flight; instrument, troubleshoot, and characterize filter behavior from telemetry and logs.

Basic Qualifications

• Education: MS in Aerospace Engineering, Electrical Engineering, Mechanical Engineering, Robotics, Computer Science, or a related field, ideally with a concentration in estimation, navigation, or sensor fusion.
• Experience: 2+ years of professional experience, with an MS, developing state estimation and sensor fusion systems for dynamic platforms.
• Estimation Depth: Hands-on expertise with Kalman-class estimators, including EKF/UKF, and the underlying theory, including process and measurement modeling, observability, tuning, and consistency analysis, applied to real systems rather than textbook problems.
• Mobile or Field Robotics Estimation Experience: Direct experience developing state estimation for mobile or field robotics platforms, including ground, aerial, legged, or marine systems, operating in real-world conditions with onboard sensing and motion.
• Real-System Validation: A track record of taking estimators beyond simulation onto hardware and validating them against flight or experimental truth data.
• Software Skills: Strong C++ for on-vehicle implementation and Python for analysis and simulation.
• Travel: Ability to travel as necessary to support rigorous flight testing events and campaigns.

Preferred Qualifications

Experience in any of the following areas is a plus:

• Education: PhD in a relevant field with a research focus in estimation, navigation, or sensor fusion.
• GPS-Contested & Denied Navigation: Direct experience maintaining a trustworthy state as GNSS degrades or disappears, including alternative navigation, integrity monitoring, or anti-jam/anti-spoof awareness.
• Target Tracking: Relative-state estimation against maneuvering targets, including high-G or high-closing-rate engagements.
• Advanced Estimation Methods: Factor graphs, fixed-lag smoothing, GTSAM/Ceres or equivalent, and visual-inertial odometry (VIO).
• Embedded & Real-Time Deployment: Estimators running on resource-constrained targets, including STM32, Jetson, and FPGA platforms, under RTOS/Linux, with attention to timing, fixed-point/numerical issues, and high-rate telemetry.
• Simulation & Validation: High-fidelity physics modeling and digital-twin replication for estimator development and SITL/HITL validation.
• Flight Regimes: High-speed multirotor or rocket systems; nonlinear dynamics and transition maneuvers.
• Software Frameworks: ROS/ROS2 or other custom, lightweight middlewares.

Export Control

This position may involve access to technology, material, technical data, defense articles, or information subject to U.S. export-control laws, including the International Traffic in Arms Regulations (ITAR), the Export Administration Regulations (EAR), and applicable contract requirements. Assignment to covered work is contingent upon the company's ability to verify that the candidate is authorized to receive access to such items or information, including by qualifying as a "U.S. person" as defined in 22 C.F.R. 120.62, or through any required export-control authorization, notice, approval, or access-control process.