QA Engineer for AI Training (Remote)
Listing checked September 10, 2026 · pay as published by Micro1
Overview
micro1 seeks QA Engineers to support a high-volume project that trains next-generation AI systems. You will evaluate AI-generated technical outputs against rubrics, design test cases, and document defects. The role is fully remote and open to candidates with strong QA backgrounds plus prior paid experience in human data annotation, RLHF, or model evaluation. No AI experience is needed, but software QA alone without a human-in-the-loop AI component does not meet the requirement.
What You'll Do6
- 1Rate AI-generated technical answers using defined quality criteria, spotting responses that look correct but contain inaccuracies or gaps.
- 2Create and review test cases for functional, regression, and edge-case scenarios, including negative and boundary tests.
- 3Examine bug reports and test documentation to confirm issues are reproducible, complete, and correctly prioritized.
- 4Isolate and document defects with clear reproduction steps, using structured tracking tools.
- 5Write detailed annotations and feedback that developers can act on without asking for clarification.
- 6Work with project teams to improve evaluation guidelines and testing standards.
Requirements8
- 1Professional experience as a QA Engineer, SDET, Test Engineer, QA Analyst, or similar role.
- 2Solid grasp of QA fundamentals: test case design, bug tracking, regression testing, and manual plus automated testing.
- 3Hands-on use of automation frameworks and test management tools such as Selenium, Playwright, Cypress, Appium, Postman, Jira, TestRail, Zephyr, or BrowserStack.
- 4Prior paid human data experience for AI training, including annotation, labeling, RLHF, AI response evaluation, model evaluation, or rubric-based grading. This is a firm project requirement.
- 5Strong analytical and problem-solving skills with close attention to detail.
- 6Ability to explain complex findings in written English at B2 level or above, giving specific, actionable feedback.
- 7No degree required. Practical, demonstrable testing experience matters more.
- 8Reliable internet connection and readiness to start soon.
Who Should Apply
This role fits QA professionals who have already worked on paid human data projects for AI training, such as annotation, RLHF, or rubric-based grading, and who can point to hands-on use of tools like Selenium, Jira, or TestRail. It is less suitable for candidates whose QA experience is limited to traditional software testing without any human-in-the-loop AI evaluation component. A common reason applicants get rejected is missing that paid human data requirement, even when their QA background is strong. Another is providing vague feedback examples instead of specific, reproducible defect reports.
Salary Insight
Compensation is $90 to $175 per hour. The final rate depends on your experience and the project scope.
Pay and demand for Machine Learning & AI roles
AggregatedTypical pay
$70/hour
This role
$90–$175/hr
Most Machine Learning & AI roles pay $50–$95 per hour. This role's pay sits above that range.
Based on 616 similar roles that publish pay · 166 publish only a top rate; those count at the rate they gave
Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.
- Live similar roles
- 680
- Listed in last 30 days
- 345
- Remote
- 98%
Hiring most right now: micro1 (273) · SME Careers (137) · Mercor (87)
Most requested skills · share of roles
- llm evaluation17%
- ai training16%
- python15%
- trainer feedback12%
Figures from Machine Learning & AI roles live on NearSkill when this page loaded. A role can close before you apply, so check the listing itself.
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Compensation
$90–175/hr
Required Skills
Application Tip
In your application, highlight at least one paid human data project where you performed annotation, RLHF, or rubric-based grading, and name the exact tools you used, such as Selenium, Jira, or TestRail. Quantify your impact, for example the number of test cases you designed or defects you documented, to show fit for this evaluation-heavy role.
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