I’m Mohamed Kamal Farag, a detail-oriented and tech-savvy data annotator focused on improving AI outputs through high-quality text, audio, transcription, and evaluation work. I enjoy following complex guidelines carefully, keeping consistency across formats, and making sure labeled data and reviewed responses meet strict quality standards.
Over the past few years, I’ve contributed remotely to AI training and data evaluation projects—transcribing English and Arabic audio for speech-to-text workflows, validating segmented datasets for ASR-related tasks, and evaluating chatbot responses for clarity, relevance, and accuracy. I also support large-scale labeling and review work across multiple platforms, maintaining strong quality scores while delivering batches reliably on deadline.
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