Remote Data Labeler
VideoRLHF
Remote video labeling project focused on preparing high-quality training data for Reinforcement Learning from Human Feedback (RLHF) systems. The work involved reviewing video clips, evaluating content against detailed guidelines, tagging actions, behaviors, context, relevance, and quality signals, and helping rank or classify outputs to improve AI model performance. The project required strong attention to detail, consistency, fast decision-making, and accurate handling of large volumes of multimedia data in a fully remote environment.
Remote video labeling project focused on preparing high-quality training data for Reinforcement Learning from Human Feedback (RLHF) systems. The work involved reviewing video clips, evaluating content against detailed guidelines, tagging actions, behaviors, context, relevance, and quality signals, and helping rank or classify outputs to improve AI model performance. The project required strong attention to detail, consistency, fast decision-making, and accurate handling of large volumes of multimedia data in a fully remote environment.
2026 - Present