AI Trainer and Data Annotation (Remote)
Provided AI response evaluation by reviewing generated outputs for clarity, coherence, analytical depth, and academic-standard alignment. Designed and used structured tasks to assess model reasoning quality and written output performance. Identified failure cases such as weak reasoning, superficial interpretation, unsupported claims, and stylistic inconsistencies. •Reviewed AI-generated responses against quality benchmarks •Authored structured written feedback to guide improvements •Performed failure-case analysis to inform model QA •Worked asynchronously within a deliverables-driven framework