AI Training and Data Annotation Specialist
Labelbox
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RLHFI performed large-scale data labeling and annotation specializing in text, image, audio, and video data for AI and machine learning model training. My responsibilities included prompt-response evaluation, response ranking, and reinforcement learning from human feedback (RLHF) for advanced AI systems. I developed annotation guidelines, evaluated dataset quality, and ensured high accuracy in ground-truth datasets essential for LLMs, NLP, and computer vision models. • Designed and maintained annotation protocols for consistent, reliable labeling outcomes. • Conducted quality assurance checks and dataset validation processes across multiple projects. • Collaborated with distributed annotation teams and contributed to scalable data annotation workflows. • Utilized industry-leading platforms like Labelbox, CVAT, Prodigy, SuperAnnotate, Doccano, and AWS SageMaker Ground Truth.