Principal Engineer, State Estimation

What you'll do

• Develop and implement advanced state estimation algorithms, including inertial navigation, sensor fusion, and alternative navigation techniques for denied environments.
• Design and optimize state estimation frameworks to integrate data from IMUs, GNSS receivers, visual odometry, magnetometers, barometers, and radar systems.
• Build real-time sensor processing pipelines for UAV platforms, focusing on robustness, accuracy, and failover performance.
• Collaborate with autonomy, software, and hardware teams to ensure seamless integration of state estimation components within larger autonomous systems.
• Lead simulation, lab testing, and field validation of state estimation algorithms to assess performance under varying operational conditions.
• Stay on the forefront of navigation and state estimation innovation—adapting emerging technologies and research into deployable, mission-ready solutions.

Required qualifications

• Typically requires a minimum of 12 years of relevant experience with a bachelor’s degree; or 10 years with a master’s degree; or a PhD with 8 years of experience; or equivalent practical experience.
• Deep experience developing real-time navigation and/or sensor fusion algorithms with IMUs, GPS, and other sensors.
• Strong understanding of state estimation techniques (e.g., Kalman filters, extended and unscented variants, particle filters, etc.).
• Proficiency with C++11 or newer; experience with real-time operating environments.
• Comfort with Linux, scripting, and standard development tools.
• Excellent communication and collaboration skills; ability to work across engineering disciplines and with external partners.
• Proven track record of successfully shipping products, showcasing the ability to navigate through development cycles, overcome obstacles, and deliver high-quality solutions to meet project deadlines and exceed expectations in a fast-paced environment.
• Demonstrated record of working hard, being a trustworthy teammate, holding yourself and others to high standards, and being kind to others.

Preferred qualifications

• Experience developing and implementing inertial navigation solutions for GPS-denied or degraded environments.
• Knowledge of computer vision techniques.
• Proficiency in optimizing algorithms for compute-constrained systems.
• Experience with CUDA or other hardware acceleration technologies (e.g. FPGAs).
• Proven track record of transitioning from R&D to production.