Gatik is revolutionizing the B2B supply chain with its autonomous transportation-as-a-service (ATaaS) solution, aiming to solve the challenges of safe, consistent, and streamlined freight movement in middle-mile logistics by reducing congestion through autonomous Class 3-7 trucks.
Requirements
- 3+ years specifically in Visual Odometry or VIO.
- 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.
Responsibilities
- 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.
Other
- This role is onsite 5 days per week at our Mountain View, CA office.
- 5+ years of experience in robotics, computer vision, or autonomy
- Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, or a related field.
- Experience working on Autonomous Vehicle platforms (e.g., development, testing, or deployment of AV systems).
- Familiarity with real-world deployment constraints such as environmental variability, sensor degradation, and compute limitations.
