AI Data Annotator – Aether Project (Outlier AI)
As an AI Data Annotator on the Aether Project, I labeled, evaluated, and ranked AI-generated outputs across multiple data types, including images, text, audio, video, and infographics, using structured annotation guidelines. My work focused on ensuring quality, accuracy, and consistency by assessing outputs for clarity, grammar, tone, and instruction adherence. I maintained strong attention to detail across repetitive tasks while identifying errors and inconsistencies in model responses. • Labeled and classified AI-generated outputs across text, audio, video, and visual formats based on predefined quality criteria • Evaluated responses for clarity, grammar, tone, accuracy, and relevance • Ranked outputs according to structured annotation and evaluation guidelines • Identified errors in reasoning, language use, and instruction compliance • Applied consistent judgment across different data types and task formats • Maintained high accuracy and consistency across high-volume annotation tasks