Senior/Staff Software Engineer – Localization (Visual Odometry)

We are looking for a Senior or Staff Software Engineer with a strong background in Visual Odometry (VO) and Localization to join our autonomy team. This role is critical to building precise, real-time vehicle localization systems using camera-based perception for autonomous driving applications. The ideal candidate has hands-on experience deploying VO systems in real-world environments, particularly in the autonomous vehicle (AV) domain, and brings solid C++ engineering skills to architect robust, high-performance software solutions. This role is onsite 5 days per week at our Mountain View, CA office. • Design and develop real-time Visual Odometry pipelines using monocular, stereo, or RGB-D camera inputs. • Implement robust camera-based localization algorithms, including visual-inertial odometry (VIO), feature tracking, motion estimation, and scale recovery. • Integrate VO systems with IMU, GPS, and other sensor data to enhance pose estimation accuracy and stability. • Collaborate with the mapping, perception, and control teams to integrate localization with the AV software stack. • Develop and optimize production-quality code in modern C++ for real-time performance on embedded compute platforms. • Analyze system performance in diverse environmental conditions and drive improvements for reliability, accuracy, and robustness. • Participate in code reviews, mentor team members, and contribute to architectural decisions. • Stay up to date with the latest research in SLAM, VIO, and VO, and help transition promising techniques into production

• Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, or a related field. • 5+ years of experience in robotics, computer vision, or autonomy; 3+ years specifically in Visual Odometry or VIO. • Experience working on Autonomous Vehicle platforms (e.g., development, testing, or deployment of AV systems). • Expert proficiency in C++ (C++14/17/20) and modern software engineering best practices. • Solid understanding of epipolar geometry, camera calibration, bundle adjustment, and optimization techniques. • Hands-on experience with open-source VO/SLAM libraries such as ORB-SLAM, VINS-Fusion, OpenVINS, or similar. • Experience working with ROS/ROS2, Linux development environments, and version control systems. • Experience integrating visual odometry with Lidar, GPS, or map-based localization. • Knowledge of GPU acceleration techniques (CUDA/OpenCV/OpenGL) for computer vision pipelines. • Familiarity with real-world deployment constraints such as environmental variability, sensor degradation, and compute limitations. • Experience in sensor calibration, time synchronization, and data preprocessing pipelines. • Contributions to relevant open-source projects or publications in VO, VIO, or SLAM. Salary Range - $170,000- $260,000