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Emotion RecognitionI have experience supporting AI training and data annotation projects by reviewing, labeling, and organizing data to improve the accuracy and performance of machine learning models. My work has involved evaluating text for relevance, categorizing information, identifying patterns, and ensuring datasets meet quality and consistency standards. I am comfortable following detailed annotation guidelines, maintaining accuracy across large volumes of data, and providing clear feedback when inconsistencies are identified. I have experience working with language-based tasks such as content review, text classification, data validation, and quality assurance.
Yes. Through my work with Outlier AI and CrowdGen, I have experience with AI training and data annotation tasks, including evaluating AI-generated content, rating responses, applying annotation guidelines, performing quality reviews, and providing feedback to improve model performance. These activities are closely related to data labeling and AI model training.
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AI Evaluation & Data Annotation Specialist – Outlier AI (Aether Project)
