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Freelancer Overview
With 3–5 years of hands-on experience in AI training data and data labeling, I bring a well-rounded skill set across the full spectrum of annotation disciplines — including text annotation and NLP, image and video labeling, audio transcription, RLHF (Reinforcement Learning from Human Feedback), and code review and evaluation. I have consistently delivered high-quality labeled datasets that support the development of accurate, reliable, and safe AI models across diverse domains and modalities. What sets me apart is my ability to work across multiple data types with equal proficiency, combined with a strong understanding of how human feedback directly shapes model behavior and performance. My experience with RLHF in particular reflects a deep engagement with modern AI alignment workflows, where nuanced judgment, consistency, and attention to guideline compliance are critical. I am detail-oriented, adaptable to evolving annotation frameworks, and committed to maintaining the data quality standards that world-class AI systems demand.