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Localization and Mapping Software Engineer

Sunnyvale, CA

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

 

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