USA remote
SLAM Engineer, Calibration, Mapping & Localization - DoorDash Dot
About this role
About the Team DoorDash Labs is an independent team within DoorDash. We are working on building autonomous delivery robots from the ground-up and other automation solutions as part of DoorDash's core delivery platform. If you have a passion for ensuring the robotic solutions used by millions of people are secure, then we want to talk to you! About the Role In this role, you will help scale our fleet of robots by advancing our large-scale HD mapping and robust localization capabilities.
This includes things like elevating HD map quality and coverage, and building highly robust relative and absolute localization systems that perform reliably in dynamic urban environments. You will operate in a fast-moving organization owning architecture, driving implementation, and helping set the technical direction. You’re excited about this opportunity because you will… Architect and deploy production-grade SLAM systems for large-scale HD maps.
Design and implement robust 3D registration pipelines for real-world, noisy, and large environments. Develop robust state estimation systems for localization handling real-world challenges. Partner cross-functionally with perception, hardware, and autonomy teams to deliver tightly integrated solutions. We’re excited about you because… B.S., M.S., or PhD. in Computer Science, Robotics or related technical field 4+ years of industry experience working within the AV, Robotics, embedded systems or equivalent industry.
Experience with C/C++ and Python. You possess deep expertise in: 3D geometry, spatial reasoning LiDAR- and/or vision-based 3D registration (ICP variants, feature-based, global registration, loop closure) Large-scale non-linear optimization State estimation (EKF/UKF, factor graphs, smoothing and filtering techniques) Nice to Have: Experience with modern deep learning algorithms and frameworks. Experience with multi-modal localization (e.g.
leveraging lidar, camera, and radar sensors to achieve robust localization). We expect this position to be filled by 9/2/26. Compensation The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location.