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Shield AI is seeking a Staff Engineer, State Estimation to research and develop state-of-the-art state estimation and navigation algorithms enabling resilient autonomy in GPS-denied environments. You will design and deploy production-grade C++ software for embedded robotic systems operating in dynamic, real-world conditions, and build rigorous unit, integration, and system-level tests to ensure robustness and safety.
Key responsibilities include developing and enhancing modeling, calibration, and simulation tools for inertial and vision-based navigation systems; contributing to roadmap planning, feature decomposition, and agile execution alongside a multidisciplinary autonomy engineering team; and continuously enhancing performance analysis, benchmarking, and validation pipelines to drive rapid innovation.
Shield AI is a venture-backed defense-tech company protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. The company operates globally with offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific.
REQUIREMENTS:
- M.S. in Aerospace Engineering, Electrical Engineering, Robotics, Computer Science, or related field; minimum 2+ years of related professional work experience if holding an M.S., or 0 years if a new Ph.D. graduate
- Professional proficiency in modern C++ (C++11 or newer) with strong object-oriented design skills
- Hands-on experience deploying low-latency C++ applications to embedded Linux platforms
- Professional experience designing and implementing state estimation algorithms (EKF, UKF, Particle Filters, graph-based optimization)
- Familiarity with VIO, SLAM, or multi-sensor fusion frameworks (GTSAM, Ceres, OpenVINS)
- Strong working knowledge of CI pipelines and automated testing frameworks for C++
- Ability to independently deploy high-reliability code for real-world autonomous systems
- Note: Primary experience in MATLAB or Python is unlikely to be a good fit; this role demands professional C++ production deployment skills
PREFERRED QUALIFICATIONS:
- Deep understanding of graph-based optimization for state estimation
- Experience developing vision-aided inertial navigation systems (VINS, VIO, Terrain Relative Navigation)
- Experience with navigation sensor calibration (IMU, GPS, barometers, magnetometers, laser altimeters, cameras)
- Experience in benchmarking and system validation for real-world navigation performance
