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MercorNo subject matter listed
AudioI specialize in bridging the gap between human insight and AI systems, with hands-on experience in data labeling, annotation, and optimizing training data for multimodal AI models, including computer vision and generative content. My work includes evaluating and ranking large volumes of AI outputs—such as images, audio, and video—using structured judgment frameworks, and applying detailed labeling guidelines to support preference-based tuning and reinforcement learning from human feedback (RLHF). I have led global teams in capturing and curating data assets for AI pipelines, ensuring alignment with both technical and creative requirements. My background in project management, creative direction, and cross-functional communication enables me to deliver high-quality, scalable annotation workflows that drive model performance and innovation. I am proficient with tools like Flowise, Monday.com, and Adobe products, and thrive in collaborative, fast-paced environments where both accuracy and creativity are valued.
Evaluated and refined LLM outputs through transcription review, quality assurance audits, and accuracy scoring.
Bachelor of Arts, International Relations
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