Data Annotation Contributor (Remote) — DataAnnotation (Ongoing)
Served as a Data Annotation Contributor performing 200+ hours of AI response evaluation for machine learning training pipelines. Reviewed and rated LLM-generated outputs for accuracy, reasoning quality, tone, clarity, and completeness while following complex, multi-criteria annotation rubrics. Built evaluation criteria including constraint types (Essential, Valuable, Nice to Have) and applied annotation taxonomies and benchmarks across high-volume workflows.• Evaluated AI responses using detailed rubrics and guideline-driven scoring• Flagged subtle errors, factual inaccuracies, ambiguous instructions, and edge cases• Wrote structured, evidence-backed rationale and improvement notes for model outputs• Conducted multi-turn conversation evaluation and system prompt quality assessment