RLHF Feedback & AI Response Quality Evaluation (Independent project)
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RLHFFreelance AI Data Labeler and Annotation QA Specialist performing supervised NLP and document labeling for financial-domain datasets. Responsibilities included text annotation, NER labeling using a defined label taxonomy, and document classification for downstream model training. The role also covered RLHF evaluation work by scoring AI assistant responses and providing structured preference signals. • Completed RLHF tasks (helpfulness, factual accuracy, safety, instruction-following) with written rationales as training signals. • Annotated 5,000+ financial text samples with >95% accuracy and applied guideline checklists to reduce disagreement. • Classified KYC forms, compliance reports, and transaction records for document-understanding model training. • Delivered annotation outputs across multiple labeling platforms while maintaining dataset quality through QA/ground-truth validation.