AI Data Annotation Specialist (LLM Evaluator & Multimodal Annotator)
Delivered LLM output evaluation work across text datasets by ranking responses for factual accuracy, instruction-following, tone, and safety. Performed rubric-based quality scoring and produced written justifications for each ranking decision. Supported RLHF-style training pipelines through consistent preference labeling. • Apply detailed rubrics for evaluation • Produce citation-free written ranking justifications • Escalate ambiguous or policy-violating samples with notes • Support downstream QA and reviewer workflows