Aaron Levine is a Senior Research Engineer based in Sudbury, Massachusetts, with eight years of experience building scalable ML systems. He currently leads production-grade ML pipelines at Rakuten, deploying and maintaining multi-GPU, multi-node clusters, and orchestrating containerized workloads with Docker, Kubernetes, and GlusterFS. He specializes in turning cutting-edge research into reusable, scalable infrastructure for large-scale search and ML workloads, including high-speed InfiniBand networking via RDMA and SR-IOV tooling. His background spans computational linguistics and mathematics, with a Master's in Computational Linguistics from Brandeis and a BA in Mathematics and East Asian Studies from Oberlin, enabling him to bridge linguistics research with practical ML engineering. He has a track record of delivering end-to-end ML systems—from data pipelines to deployment—supporting researchers and business units alike. Outside production systems, he leverages a diverse academic foundation to drive efficient, repeatable experimentation and robust observability across clusters.
9 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Mathematics and East Asian Studies, 3.4, Bachelor's degree, Mathematics and East Asian Studies, 3.4 at Oberlin College
Master's degree, Computational Linguistics, Master's degree, Computational Linguistics at Brandeis University
java, python, scheme, sql, matlab, English, Japanese, Latin, Korean
A fast build system that encourages the creation of small, reusable modules over a variety of platforms and languages.
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