In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. This opportunity is open to specialists with strong professional QA backgrounds. Prior paid experience with human data annotation, RLHF, model output evaluation, or rubric-based grading for AI training is a plus, but not required.

• Evaluate and rate AI-generated technical outputs against defined quality criteria and rubrics, identifying answers that may appear correct but are actually 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 and utilize 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 ensure continuous improvement of testing standards and methodologies.

Work arrangement: Fully remote