Data Quality Analyst

Figure AI · San Jose, CA
full-time mid Posted 10 months ago
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About this role

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA. We are looking for Data Quality Analyst  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 This is a six-month fixed-term agreement , with potential for longer-term opportunities depending on your contributions and interests. We’re looking for motivated people who want to support real-world robot development—and grow with us. The US base salary range for this full-time position starts at $30/hr.  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.

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