AI Data Annotator / AI Content & Code Quality Evaluator (Scale AI workflows, including RLHF feedback review)
Assessed AI-generated outputs for accuracy, consistency, and compliance with project guidelines, providing human feedback to support model improvement. Performed quality checks and error analysis to identify issues affecting performance and reliability. Evaluated Python scripts, functions, and algorithms for correctness, efficiency, and expected behavior. • Reviewed outputs and flagged inaccuracies, inconsistencies, and guideline violations. • Conducted QA passes to detect logical errors and performance issues. • Validated code outputs to ensure functionality and reliability. • Recommended improvements based on Python coding standards and best practices.