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Freelancer Overview
I am an experienced AI data trainer and annotator with over three years of hands-on expertise in supporting the development of large language models and multimodal AI systems. My background includes supervised fine-tuning (SFT), reinforcement learning with human feedback (RLHF), prompt engineering, and rigorous evaluation of AI outputs to ensure quality, safety, and alignment. I have worked extensively on data annotation and curation across text, image, video, and audio modalities, with a strong focus on bias reduction, data quality, and reliable AI performance in both multilingual and STEM-oriented domains. My experience spans object detection, bounding box annotation, sentiment analysis, content categorization, and professional scenario modeling for AI. I have contributed to projects involving computer vision, natural language processing, and cross-lingual model training, consistently maintaining high standards for dataset integrity and annotation quality. I am adept at collaborating with cross-functional teams, structuring datasets for optimal training workflows, and providing actionable feedback to drive continuous model improvement.
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