Data Annotation
Annotated video datasets to assess emotional authenticity and behavioral naturalness of AI-generated actions, flagging ambiguous or unnatural sequences to improve model realism and human-likeness
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I am an experienced AI training data specialist with a strong background in data annotation, multilingual labeling, and LLM training across healthcare, technology, and retail sectors. My expertise includes annotating and transcribing diverse datasets—spanning text, image, and audio—using advanced tools and Linux/Ubuntu environments to support reinforcement learning from human feedback (RLHF) and model fine-tuning. I have contributed to high-quality AI projects, such as English-Swahili localization for NLP models and prompt evaluation for large language models, ensuring cultural relevance and accuracy. My skills in CRM tools like Zendesk, Zoho, and HubSpot, combined with my ability to collaborate with researchers and QA teams, help me deliver precise, actionable data that drives AI model improvements and aligns with project goals.
Annotated video datasets to assess emotional authenticity and behavioral naturalness of AI-generated actions, flagging ambiguous or unnatural sequences to improve model realism and human-likeness
Bachelor of Science, Horticulture
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