We are seeking experienced QA Engineers to contribute their expertise in software quality evaluation for a high-volume project focused on training next-generation AI systems. In this role, you will help shape how AI models learn, reason, and perform by providing high-quality, real-world input and evaluation.
Required experience: This role requires prior paid experience with human data annotation, Reinforcement Learning from Human Feedback (RLHF), model output evaluation, or rubric-based grading for AI training. General software QA experience alone, without a human-in-the-loop AI evaluation component, does not meet the requirements for this project. Prior AI development experience is not required; domain knowledge and evaluation skills are key.
Scope of Work
Evaluate and rate AI-generated technical outputs against defined quality criteria and rubrics, identifying answers that may appear correct but are inaccurate or incomplete.
Design and assess comprehensive test cases for functional, regression, and edge-case scenarios, including negative and boundary tests.
Review bug reports and test documentation to ensure issues are reproducible, documentation is complete, and severity is properly assessed.
Identify, isolate, and document defects with precise reproduction steps using structured tracking mechanisms.
Provide detailed, actionable written feedback and annotations to support efficient resolution by developers without the need for clarification.
Collaborate with project teams to refine evaluation guidelines and continuously improve testing standards and methodologies.
Qualifications
Prior paid human data experience supporting AI training—such as annotation, labeling, RLHF, AI response evaluation, model evaluation, or rubric-based grading—is required.
Professional experience as a QA Engineer, SDET, Test Engineer, QA Analyst, or in a similar software quality assurance role.
Strong command of QA fundamentals, including test case design, bug tracking, regression testing, and manual and automated testing strategies.
Hands-on experience with automation frameworks and test management tools such as Selenium, Playwright, Cypress, Appium, Postman, Jira, TestRail, Zephyr, or BrowserStack, or similar tools.
Strong analytical and problem-solving skills and meticulous attention to detail.
Ability to communicate complex findings clearly in written English (B2 level or above), with specific, actionable feedback.
No formal degree is required; practical, demonstrable testing experience takes precedence.
Reliable internet connection and readiness to begin promptly.
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