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Freelancer Overview

I have hands-on experience working with AI training data pipelines, particularly in designing, structuring, and validating high-quality datasets for supervised learning and retrieval-augmented generation (RAG) systems. My work has included curating datasets for prompt injection testing, crafting synthetic examples to expose edge cases, and implementing evaluation workflows to assess model accuracy and robustness. I understand the importance of balanced, unbiased, and well-annotated data in training performant AI systems, and I bring a methodical, test-driven mindset to dataset design. What sets me apart is a strong blend of technical expertise and AI research insight. I have built tools for structured data extraction from unstructured inputs (like email), experimented with AI-driven labeling workflows, and published detailed findings on Medium to share my methodologies. My background in AI, paired with software development and cloud deployment skills, allows me to contribute to both the data preparation and infrastructure sides of the training pipeline.

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