I’m an AI Training Specialist and data annotation expert with 4+ years of experience helping improve large language model quality through response ranking, prompt evaluation, fact-checking, and RLHF-style feedback workflows. I apply detailed written guidelines to assess AI-generated text, audio, video, and multimodal content for accuracy, relevance, safety, and policy compliance—while consistently maintaining very high QA accuracy on large-scale datasets.
I also bring strong hands-on experience in labeling and quality assurance for video and robotics/autonomous systems data, including frame-accurate video annotations and multimodal sensor labeling (camera feeds, LiDAR point clouds, and robotic trajectories). I’m comfortable working fully remote with distributed teams, resolving edge cases using clear documentation and structured reporting, and supporting ML training outcomes across research and real-world domains.
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