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Freelancer Overview

I am an experienced machine learning engineer with a strong background in building end-to-end pipelines for data labeling, annotation, and AI training data management. My work spans automating data ingestion, preprocessing, and evaluation for large-scale LLM fine-tuning and scientific ML projects, using tools like Python, PyTorch, Hugging Face Hub, W&B, and AWS. I have developed reproducible workflows that ensure high-quality, schema-validated datasets—such as generating and labeling 100k synthetic protein sequences and QA pairs for domain-specific models. My expertise includes optimizing data pipelines for efficiency and accuracy, supporting robust model training and deployment in domains like scientific ML and NLP. I am passionate about creating practical systems that accelerate the journey from raw data to high-performing AI models.

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