State Estimation Engineer, Shield AI

• We are seeking engineers with a strong foundation in state estimation theory and practical experience deploying robust, real-time solutions in commercial robotics, SLAM, or related autonomy applications
• 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 have 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, 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

Desirable

• . As a Senior Engineer, you will play a critical role in designing, developing, integrating, testing, and deploying cutting-edge navigation and state estimation algorithms within our Hivemind SDK
• 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