Figure
Localization and Mapping Software Engineer
Figure, Sunnyvale, California, 94087
Figure is an AI Robotics company developing a general purpose humanoid. Our Humanoid is designed for corporate tasks targeting labor shortages and jobs that are undesirable or unsafe. We are based in Sunnyvale, CA and require 5 days/week in-office collaboration. Figure's vision is to deploy autonomous humanoids at a global scale. Our AI team is looking for Localization and Mapping Software Engineers to empower Figure humanoid robots to perform highly dynamic operations in demanding real-world environments. Responsibilities: Design, implement, test, and deploy localization and mapping algorithms for humanoid robots, fusing information from cameras, IMUs and other sensors Own tracking and odometry modules at Figure Implement onboard, real-time tracking and odometry software Build evaluation pipelines, including data collection and metrics, in collaboration with other Figure teams Engineer and ship high quality, reliable software that will be deployed to the real world Collaborate with other Figure team members to develop and continuously improve the full autonomy stack Requirements: Have a deep knowledge of classical computer vision techniques (feature detection, stereo matching, structure from motion etc) Industry experience building robust odometry applications, preferably visual inertial odometry Familiar with Deep Learning techniques for Localization and Mapping applications, especially feature detection and pose regression Hands-on experience with sensor calibrations (e.g. stereo cameras, camera and IMU extrinsics) Capable of quickly writing massive amounts of high quality, well-tested, perception software Thrive in a high pace environment, where solutions are often unclear and require exploration Passionate about building humanoid robots Bonus Qualifications: Experience with addressing edge cases from localization and mapping solutions deployed at scale Experience with the initialization of visual inertial odometry Research background in SLAM and/or publications in localization and mapping applications