Principal Engineer - Visual Mapping and Localization

Motional•San Francisco, CA

4d•$240,000 - $330,000•Hybrid

About The Position

On our Spatial Intelligence Team, you’ll have the opportunity to work with world-class 3D computer vision and machine learning engineers, whose mission is to make self-driving vehicles a reality and to create a positive social impact. The team creates computer vision-derived world maps, fuses vision-derived maps with LIDAR-based maps, updates these maps as the world changes, and localizes autonomous vehicles within these maps in real-time. We are looking for proven technical experts who are passionate about Level 4 autonomous driving technology, excited by intellectual challenges, and are interested in pursuing career growth in a fast-growing company.

Requirements

Experience developing software for geometric computer vision - geometric camera models, camera calibration, fundamental / essential matrices, the epipolar constraint, feature detection and matching, triangulation
Experience with visual simultaneous localization and mapping (VSLAM), structure from motion, visual-inertial SLAM, visual-inertial odometry, and large-scale bundle adjustment/factor graph optimization at scale
Proven track record of designing, developing and deploying 3D computer vision solutions for autonomous vehicles, augmented reality, robotics or related applications
Masters or Ph.D. in Computer Science or a related technical field; or equivalent industry experience
7+ years of professional software engineering experience.
Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods
Extensive experience in metrics design and metrics driven technology development
Excellent communication and interpersonal skills
Strong programming skills in C++
Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, WACV, AAAI, ICL, etc.)

Nice To Haves

Experience with multi-modality, multi-sensor fusion-based mapping, e.g. visual + LIDAR-based mapping
Remote sensing experience including geospatial coordinate frames, RPC camera models
Strong python programming skills
Experience training ML models using Pytorch or other libraries

Responsibilities

Define, lead and execute computer-vision based mapping projects that improve our self-driving vehicles’ capability to efficiently map roadways and localize itself using vehicle and remote sensing data
Develop methods to monitor changes to the environment and update maps accordingly
Integrate visual maps with LIDAR-derived maps to create consistent fused world maps
Productionize and deploy solutions onto autonomous vehicle fleets
Collaborate with LIDAR-based localization and mapping, and perception teams to improve our vehicle’s on-road performance