Michael Sugimura
Machine Learning Engineer at 2389 Research
Greater Chicago Area United States
Summary
👤
Senior🎓
Top SchoolMichael Sugimura is a machine learning engineer and founder with eight years of experience building production-grade computer vision, NLP, and deep learning systems across e-commerce, consulting, and government domains. He currently leads ML efforts at 2389 Research and is the founder of Eldritch Assembly, blending hands-on research with entrepreneurship. Previously, he pioneered a multi-task, multi-modal training framework and open-source tooling for large neural ensembles at ShopRunner, and applied object detection and attribute modeling to fashion use cases at Wayfair and LTK. With a BA in Linguistics from Dartmouth and an MA in Public Policy Analysis from Georgetown, he uniquely combines linguistic insight and policy-aware thinking to data-driven solutions. Based in the Greater Chicago area, he has a track record of turning complex data into scalable, application-ready systems and leads cross-disciplinary teams toward measurable impact.
8 years of coding experience
9 years of employment as a software developer
Master's Degree Public Policy Analysis, Master's Degree Public Policy Analysis at Georgetown University
Github Skills (34)
implicit10
file-processing10
datascience10
image-text10
recommender8
computer-vision8
image-processing8
feature-extraction8
machine-learning7
recommender-system7
deep-learning7
python7
jupyter-notebook6
pipeline6
recommender-systems6
Programming languages (2)
Github contributions (5)
sugi-chan/siege_mask_rnn
Aug 2018 - Jun 2019
Contributions:10 commits, 8 pushes, 1 branch in 10 months
sugi-chan/multi_label_pigeon
Sep 2019 - Jun 2020
jupyter based annotator for multi-class multi-label image problems
Contributions:30 commits, 1 PR, 25 pushes in 10 months
annotationsimage-labeljupyter-notebookproblemsannotator
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