AI Data Contributor — Toloka/Mindrift Annotation Projects
Responsible for applying domain expertise to AI data annotation, text evaluation, and model training, with a particular focus on ecological and environmental content. Utilized structured observation protocols and followed complex guidelines to ensure accuracy in data labeling and annotation tasks, contributing to the improvement of AI models in environmental research. Delivered consistent, verifiable outputs aligned with academic and institutional requirements while using reputed third-party platforms for annotation work. • Participated in RLHF (Reinforcement Learning from Human Feedback) and content rating projects on Toloka and Mindrift platforms. • Carried out ecological and environmental text labeling tasks, including classifying, rating, and evaluating scientific content. • Collaborated with teams and managed task allocations in annotation projects considering large-scale academic research protocols. • Produced detailed, structured reports for labeled datasets in environmental and forestry domains.