Job Description
The role involves designing and developing real-time visual odometry and localization systems for autonomous vehicles, integrating sensor data to ensure precise vehicle positioning, and collaborating with cross-functional teams to enhance autonomous driving software.
Key Responsibilities
- Design and develop real-time Visual Odometry pipelines using camera inputs.
- Implement camera-based localization algorithms, including visual-inertial odometry, feature tracking, and motion estimation.
- Integrate VO systems with IMU, GPS, and other sensor data to improve pose estimation.
- Collaborate with mapping, perception, and control teams to integrate localization into the AV software stack.
- Develop and optimize high-performance, production-quality C code for embedded platforms.
- Analyze system performance across diverse environmental conditions and improve reliability and accuracy.
- Participate in code reviews, mentor team members, and contribute to architectural decisions.
- Stay current with research in SLAM, VIO, and VO, and transition promising techniques into production.
Requirements
- Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, or a related field.
- At least 5 years of experience in robotics, computer vision, or autonomy.
- At least 3 years of experience specifically in Visual Odometry (VO) or Visual-Inertial Odometry (VIO).
- Experience working on Autonomous Vehicle platforms, including development, testing, or deployment of AV systems.
- Expert proficiency in C, C++14, C++17, C++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 or ROS2, Linux development environments, and version control systems.
- Ability to design and develop real-time Visual Odometry pipelines using monocular, stereo, or RGB-D camera inputs.
- Ability to implement robust camera-based localization algorithms, including visual-inertial odometry, feature tracking, motion estimation, and scale recovery.
- Experience integrating VO systems with IMU, GPS, and other sensor data to improve pose estimation accuracy and stability.
- Ability to analyze system performance in diverse environmental conditions and drive improvements for reliability, accuracy, and robustness.
Benefits & Perks
Salary range of 170,000-260,000 USD
Onsite work schedule, 5 days per week
Collaborative and inclusive work environment emphasizing respect, agility, and diversity
Opportunities for professional growth through mentorship, architectural involvement, and staying current with research
Contributing to innovative autonomous vehicle technology and industry leadership
Ready to Apply?
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