Localization and Mapping Software Engineer

Key Skills

Algorithms, Apache Kafka, AWS, Azure, Deep Learning, DevOps, Figma, Regression Analysis, SLA

Job Description

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