AI Data Annotator
Fact check the response of AI responses to users using LLMs
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I am a detail-oriented professional with hands-on experience in data annotation, content evaluation, and AI training data preparation. My work with Welocalize, CrowdGen (Previously Appen), and Mercor has allowed me to develop strong skills in labeling data for machine learning, evaluating search data relevance, and generating high-quality spoken descriptions for image-based projects. I am adept at following complex guidelines, adapting to evolving standards, and ensuring both productivity and quality in remote environments. My technical skills include proficiency with R Studio and BORIS software, and I am comfortable collaborating with AI researchers and QA teams to improve data quality. With a background in ecology and multidisciplinary science, I bring analytical thinking, research expertise, and strong communication skills to every project.
Fact check the response of AI responses to users using LLMs
Shaping how Al learns to interact with real-world applications and systems like Linear, Jira, and Gorgias. Supporting the training of an AI model by improving its decision-making processes within a structured workflow of actions in a digital environment.
Develop a high-quality dataset of prompt/response conversations designed to advance Large Language Model performance across generalist, professional, and academic domains.
Develop a written transcription on various short videos. Compared which audio sounded the best
Compare two sets of images generated by the AI and choose which one looks more natural compared to the other
Bachelor of Science, Ecology and Conservation Biology
Associate Degree, Multidisciplinary Science
AI Data Annotator