Staff Engineer, State Estimation (R5783)

Help build the intelligence that enables autonomous systems to navigate the world with confidence. In this role, you’ll develop cutting-edge estimation and navigation technology, transforming advanced algorithms into high-performance software that powers resilient autonomy in complex, real-world environments.

What you'll do:

• 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.

Required qualifications:

• 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.

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.