ML Annotation QA Engineer
Gather AI (company site, opens in a new tab)2–5 yrsRemoteDirect career pageEst. 10–18 LPA
Posted on 4 Sept
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Job description
Structured overview of role & requirements
About This Role
- Own the quality analysis of annotated data for computer vision and machine learning programs, including daily review and root cause determination.
- Develop, version, and maintain verdict taxonomies, decision rules, and quality guidelines for annotation categories.
- Build and manage performance trackers to monitor error rates by facility, site, equipment, and data format, perform anomaly detection, and report findings with reproducible evidence promptly.
Minimum Requirements
- BS in Computer Science/Engineering, Electrical Engineering, or equivalent experience.
- 2–5 years experience in ML QA, annotation quality, data quality, or analytics at an AI/ML company.
- Proficient in Python and SQL (or equivalent) for querying and analyzing data independently.
- Experience assessing label quality on annotated datasets for computer vision/machine learning.
Ideal Candidate Profile
- Experienced in working directly with annotation vendors and responsible for in-house judgment-heavy quality control in ML annotation.
- Strong analytical skills with proven ability in root cause analysis distinguishing annotation errors from model or field degradation.
- Comfortable creating and evolving annotation quality processes, guidelines, and tooling to reduce manual work and improve annotation accuracy.