Data Annotation & Quality Reviewer
Annotated and evaluated multimodal data (images and text) to support reinforcement learning from human feedback (RLHF) pipelines for large language models. • Performed preference ranking and quality review tasks, ensuring annotations followed strict, structured guidelines with high accuracy and consistency. • Identified ambiguities, edge cases, and low-quality inputs, flagging issues to improve dataset reliability and model training outcomes. • Maintained high attention to detail across fast, short-form tasks while meeting productivity and quality benchmarks.