Localization and Mapping Software Engineer at Figure
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Filter by:
robot
Deep Learning
computer vision
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.Ā
Figureās 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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