I am a freelance Video Annotator with extensive experience in analyzing results produced by multimodal AI, as well as interpreting input text, pictures, and video using AI. I have worked on annotating large volumes of video, image, and audio data, using CVAT AI and internal proprietary tools, and ensuring high-quality outputs. I typically generate frame-level captions with precise action timing, label shot types and scene structure, and verify outputs against project guidelines to maintain data integrity.
I am motivated by Twine’s mission to empower creators via AI. I am self-driven, capable of meeting daily and weekly goals, and comfortable collaborating with project managers and quality leads to refine guidelines and ensure consistency. I value attention to detail and cultural alignment, and I strive to deliver accurate annotations that align with project requirements and support model improvement.
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