AI Data Annotator & Trainer
Evaluated and rated AI-generated STEM responses for factual accuracy, coherence, and quality. Participated in comparative analysis of model outputs to support RLHF pipelines in biology, bioinformatics, and general science. Labeled scientific text for text classification, NER, sentiment annotation, and content review. • Consistently flagged factual inaccuracies in science content following rigorous guidelines. • Maintained high task accuracy exceeding platform benchmarks. • Managed large-scale data labeling projects remotely. • Applied specialist biology knowledge in annotation workflows.