AI Data Annotator / Evaluator — TELUS International
Evaluated AI-generated outputs for quality, accuracy, and alignment with human intent as part of LLM training workflows. Performed data labeling tasks including ranking and prompt-response review using rubric and scorer consistency requirements. Applied native Hausa cultural and linguistic knowledge to ensure localized relevance for Hausa-speaking contexts.• Assessed outputs against quality and intent criteria• Labeled and ranked prompt-response pairs for model improvement• Reviewed tasks across multiple platforms with attention to rubric guidelines• Ensured consistent scoring behavior with alignment to human intent