On remote AI evaluation projects, I completed 10,000+ tasks across finance, reasoning, coding, and general knowledge, assessing model responses against detailed quality rubrics.
I evaluated LLM responses, ranked preferences for RLHF workflows, and compared models to identify hallucinations, reasoning errors, and factual inconsistencies. I also created reusable evaluation templates and quality processes that improved reviewer consistency and reduced turnaround time by approximately 25%.
As a Senior Data Annotation Specialist on remote AI data projects, I annotated and validated 250,000+ text, image, and document records for machine learning datasets. I maintained 99% annotation accuracy and reviewed complex data to correct labeling inconsistencies.
Earlier, as an AI Data Quality Analyst and Legal Document Review Specialist, I validated training datasets, prepared quality reports, and extracted structured information from legal records. I use Python and Excel to analyze evaluation trends and identify recurring model failure patterns.
