Overview
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy sof
Full job description
Shield AI is a venture-backed defense-tech company with the mission of 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. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
Research and develop state-of-the-art state estimation and navigation algorithms to enable resilient autonomy in challenging GPS-denied environments. Design and deploy production-grade C++ software for embedded robotic systems operating in dynamic, real-world environments. Build and maintain rigorous unit, integration, and system-level tests to ensure system robustness and safety. Develop and enhance modeling, calibration, and simulation tools for inertial and vision-based navigation systems. Contribute to roadmap planning, feature decomposition, and agile execution alongside a multidisciplinary team of autonomy engineers. Continuously enhance performance analysis, benchmarking, and validation pipelines to drive rapid innovation and improvement.
M.S. in Aerospace Engineering, Electrical Engineering, Robotics, Computer Science, or a related field; minimum 2+ years of related professional work experience if you have an M.S. degree, or 0 years if you are a new Ph.D. graduate. Professional proficiency in modern C++ (C++11 or newer) and 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 (e.g., EKF, UKF, Particle Filters, graph-based optimization). Familiarity with VIO, SLAM, or multi-sensor fusion frameworks (e.g., GTSAM, Ceres, OpenVINS). Strong working knowledge of CI pipelines and automated testing frameworks for C++. Ability to independently deploy high-reliability code suitable for real-world autonomous systems. Familiarity with prototyping in Python or MATLAB is welcome, but this role demands professional C++ production deployment skills. Candidates whose primary experience is in MATLAB or Python are unlikely to find this position a good fit.
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.
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