Mahfuzur Rahman is a Principal Machine Learning Engineer with a Ph.D. in Computer Science and over a decade of experience building production ML and LLM-based systems for Meta, Lowe’s, Samsung, and Microsoft. He designs end-to-end pipelines—RAG, evaluation frameworks, monitoring, and MLOps—that have materially improved iteration speed, latency, and quality for messaging and retail GenAI products. Equally comfortable in research and production, he has nine journal publications (including Science) and a track record of translating biological data insights into deployed models during his PhD. He mentors and hires engineers, leads cross-functional initiatives, and contributes as an editor for the Journal of Open Source Software while volunteering on impactful Omdena projects. Notably, his work on automated LLM evaluators and multilingual synthetic data sampling established organization-wide best practices used by 50+ engineers.
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