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Freelancer Overview

With over 17 years of experience in AI, machine learning, and cloud architecture, I have led and delivered large-scale projects where high-quality data labeling and annotation were critical to building robust AI and deep learning models. My work spans domains like computer vision, NLP, healthcare, and automotive, where I have overseen the creation and curation of training datasets for tasks such as image segmentation, defect detection, predictive analytics, and generative AI applications. I am skilled in leveraging Python, TensorFlow, PyTorch, OpenCV, and Hugging Face Transformers, and have integrated MLOps pipelines on Azure to streamline data preparation and model deployment. My hands-on approach includes collaborating with data scientists and annotators to define labeling guidelines, ensuring data quality, and optimizing workflows for large-scale annotation projects. I am passionate about building reliable AI systems by ensuring the integrity and accuracy of training data, and thrive in environments that value innovation, collaboration, and continuous improvement.

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