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Freelancer Overview

I am a computer science graduate student with hands-on experience in designing and implementing AI-driven solutions for real-world problems, particularly in computer vision and data annotation. My work as a lead machine learning engineer on a National Science Foundation-funded project involved developing a molecular forensics pipeline for species identification, where I achieved high-accuracy classification using Vision Transformers and optimized data processing pipelines for low-latency, real-time inference. I have a strong background in building scalable data systems and RESTful APIs, working with tools like Python, SQL, AWS, Docker, and React to manage and process large datasets efficiently. My experience spans data preparation, annotation workflows, and deploying AI models in resource-constrained environments, making me adept at creating robust and accessible AI training data pipelines.

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