Data Lead

at Figure AI · Robotics · AI - Helix Team

Figure AI is seeking a Data Lead to manage the annotation and labeling of data for AI training applications, specifically for their humanoid robots. The role involves using proprietary tools to label objects, poses, and interactions in images/videos, collaborating with ML engineers on guidelines, identifying edge cases, and ensuring quality and throughput in annotation batches.

What you'd actually do

  1. Use proprietary annotation tools to label objects, poses, and interactions in images and video streams from our humanoid robots
  2. Collaborate with ML engineers to refine labeling guidelines and improve interface efficiency
  3. Identify and flag ambiguous or edge-case scenarios for review by the ML team
  4. Maintain high throughput and consistent quality across large annotation batches
  5. Contribute feedback on workflow improvements and tool enhancements

Skills

Required

  • Strong attention to detail
  • ability to apply consistent logic across diverse scenarios
  • Comfortable navigating computer-based tools
  • quickly learning new software
  • Patient, quality-focused mindset
  • ability to juggle multiple assignments
  • Clear written and verbal communication skills
  • Reliable, self-motivated work style
  • collaborative spirit

Other signals

  • annotating and labeling data for AI training applications
  • label objects, poses, and interactions in images and video streams
  • refine labeling guidelines and improve interface efficiency
  • Maintain high throughput and consistent quality across large annotation batches
Read full job description

Figure is an AI Robotics company developing a general purpose humanoid. Our humanoid robot, Figure 02, is designed for commercial tasks and the home. We are based in San Jose, CA. It’s time to build.

We are looking for a Data Lead to help us in our efforts to annotate and label our data for AI training applications.

Responsibilities:

  • Use proprietary annotation tools to label objects, poses, and interactions in images and video streams from our humanoid robots
  • Collaborate with ML engineers to refine labeling guidelines and improve interface efficiency
  • Identify and flag ambiguous or edge-case scenarios for review by the ML team
  • Maintain high throughput and consistent quality across large annotation batches
  • Contribute feedback on workflow improvements and tool enhancements

Requirements:

  • Strong attention to detail and the ability to apply consistent logic across diverse scenarios
  • Comfortable navigating computer-based tools and quickly learning new software
  • Patient, quality-focused mindset with the ability to juggle multiple assignments
  • Clear written and verbal communication skills
  • Reliable, self-motivated work style and a collaborative spirit within a fast-paced environment
  • Fluency in English required

The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.