<p>Join our Self-Driving team to help shape one of the most advanced and widely-deployed computer vision systems in the world. As a key contributor, you will drive innovation in geometric vision, tackling challenges related to both the vehicle dynamics and environmental perception.</p> <ul> <li> <p>Develop and refine models for estimating geometric entities using both modern neural network-based and classical vision techniques</p> </li><li> <p>Leverage vast amounts of fleet data for algorithm development and validation</p> </li><li> <p>Design and develop automated data generation pipelines that create various high quality ground truth data for real-world perception problems</p> </li><li> <p>Deploy and scale your work across millions of autonomous vehicles worldwide</p> </li><li> <p>Collaborate closely with a high-caliber team dedicated to realizing full autonomy</p> </li><li> <p>Proven ability to rapidly prototype and optimize algorithms</p> </li><li> <p>Proficiency in writing production-quality code in Python</p> </li><li> <p>Proficiency in c++ is highly desirable</p> </li><li> <p>Solid understanding of linear algebra, geometry, probabilistic theory, numerical optimization, and deep learning, with hands-on implementation experience</p> </li><li> <p>Expertise in key areas of computer vision and robotics, such as structure-from-motion, Visual-Inertial SLAM, large-scale mapping and localization, dense 3D modeling, or neural rendering (e.g., NeRF, Gaussian Splatting)</p> </li><li> <p>Practical experience with PyTorch</p> </li><li> <p>Familiarity with deploying neural network models is an advantage</p> </li></ul>