or apply directly on Gather AI's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 12 days Gather AI's roles stay open a median of 45 days
- Reposted
- No
- Salary listed
- No 0% of Gather AI's roles list one
- Ghost-job risk at Gather AI
- high 11 stale, 0 reposted of 12 open
- Hiring momentum
- 17 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-09-17
Measured from postings appearing on and disappearing from Gather AI's own greenhouse board since 2026-08-03. Full hiring picture for Gather AI.
About this role
As an ML Annotation QA Engineer at Gather AI, you will be responsible for ensuring the quality of annotated data used in computer vision and machine learning programs. Your day-to-day tasks will include analyzing annotated data, conducting root cause analysis, and developing performance trackers to monitor data quality. You will collaborate closely with Machine Learning Engineers and other teams to identify and address anomalies in the data, refine decision rules, and improve annotation processes.
- benefits
- 1/5
- freshness
- 4/5
- career value
- 4/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Gather AI as an employer.
What you need
- BS in Computer Science/Engineering, Electrical Engineering, or equivalent experience
- 2–5 years of experience in ML QA, annotation quality, data quality, or analytics at an AI/ML company
- Hands-on experience with annotated ML datasets, including assessing label quality
- Demonstrated experience finding, diagnosing, and reporting data anomalies to a technical audience
- Strong understanding of statistics, and able to work with data
- Root cause analysis — generating competing hypotheses and naming the evidence that separates them
Nice to have
- 2+ years in quality assurance, data quality, or product support
- 1+ years experience with enterprise-grade ticketing systems (e.g. Jira)
- Computer vision annotation experience as a reviewer or auditor — video event labeling, bounding boxes, polygon segmentation, counting, or classification
- Annotation quality methodology — gold-set validation, inter-annotator agreement, sampling design
- Strong spatial and geometric reasoning — relevant wherever labels describe position in physical space
Worth weighing
- Role involves significant judgment and analysis that cannot be outsourced, indicating a high level of responsibility.
- The position requires a strong analytical mindset and the ability to work under ambiguity, which may not suit all candidates.
- No salary or benefits information provided in the posting.
Summarised from Gather AI's posting. Read the full original.
Listed by Gather AI on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.