Evaluating answers to prompts according to specific locale criteria.
For French(CA), French(FR) and English(CA)
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My experience with AI training and data labeling spans more than three years while I have worked on Telus International and DataAnnotation and Outlier and Mindrift platforms. My work involved evaluating and rating AI-generated content in French (CA/FR) and English (CA) by assessing factual accuracy and prompt safety as well as fluency and localization. I have performed tasks that included prompt rewriting and response classification and fine-tuning to enhance LLM output quality. I designed a structured botanical database containing more than 40,000 plant entries for an educational website through my labeling work. The classification process involved sorting species according to taxonomic categories and ecological characteristics and regional distribution data through annotation and metadata tagging methods. My work experience includes domain quality evaluation and map-based Q&A review as well as "stump-the-model" biology tasks. My scientific background combined with bilingual skills and precise work methods enable me to produce top-notch annotations for both linguistic and science-based AI projects
For French(CA), French(FR) and English(CA)
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Master's degree, Biology
Horticulturist
Research Assistant