AI Code Evaluation & NLP Data Annotation Specialist
Designed and implemented labeling schemas for NLP and code-based AI training workflows. Performed structured annotation of programming-related datasets, including code classification, intent tagging, and quality evaluation of AI-generated responses. Conducted LLM response evaluation for correctness, reasoning quality, clarity, and policy compliance. Applied multi-criteria scoring rubrics to rank outputs and identify hallucinations or logical inconsistencies. Structured labeled outputs in JSON and CSV formats for supervised training and fine-tuning processes. Performed dataset audits to resolve inconsistencies, flag ambiguous cases, and improve inter-annotator agreement. Collaborated within iterative feedback cycles to enhance data quality and support continuous model improvement.