QA & AI Evaluation Support

I’m looking for a detail-oriented tester to strengthen both my web application and the AI models behind it. Your first responsibility will be hands-on QA of the web interface, concentrating on functionality and usability. I’ll provide access to staging builds; you’ll explore user flows, replicate edge cases, and log concise bug reports with steps to reproduce, environment details, screenshots or screencasts. In parallel, I need rigorous evaluation of our AI. You’ll review and score text outputs, voice replies, and image-recognition results, flagging inaccuracies and explaining why an answer is off target. Clear, data-rich feedback is essential so the research team can iterate quickly. Where needed, you’ll annotate text, audio transcripts, or image labels to build training sets that close the identified gaps. Typical deliverables will include: • Structured bug reports in the tracker we share • A short test summary for each sprint outlining coverage and findings • AI response evaluation sheets with per-item scores and rationales • Correctly formatted annotation files ready for model retraining Familiarity with browser dev tools, common issue trackers (e.g., Jira, Trello) and basic audio or image annotation platforms will help you ramp up faster, but I’m open to comparable alternatives. Consistency, clear English, and a mindset for continuous improvement matter more than any specific tool. If you enjoy breaking things constructively and have an eye for how humans judge AI quality, this collaboration should be a perfect match.