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Freelancer Overview

I am a Computer Science Engineer specializing in ML/NLP with a focus on data integrity and model alignment. During my tenure as an ML/NLP Engineer Intern, I developed a rigorous approach to data curation and error analysis, improving model accuracy by 10% through precise dataset refinement and attention mechanism research. I am highly proficient in Python, TensorFlow, and SQL, with a deep understanding of how to identify logical fallacies, hallucinations, and edge-case failures in LLM outputs. My experience optimizing Linux-based server infrastructures and building automated MLFlow pipelines has given me a keen eye for technical efficiency and code quality. I am passionate about RLHF (Reinforcement Learning from Human Feedback) and dedicated to ensuring AI outputs are safe, accurate, and logically sound through meticulous evaluation and expert-level feedback.

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