Michael Sugimura
Machine Learning Engineer at Eldritch Assembly
Greater Chicago Area United States
Summary
👤
Senior🎓
Top SchoolMichael Sugimura is a machine learning engineer with eight years of experience applying computer vision, NLP, and deep learning to e-commerce, public sector, and research problems. He has led production ML efforts—building multi-task, multi-modal ensembles, object detection/segmentation pipelines, and GAN prototypes—at companies like ShopRunner, Wayfair, and LTK, and now runs two ventures including a research-focused role at 2389 Research. His background in public policy (Master’s from Georgetown) and linguistics (BA from Dartmouth) gives him an uncommon blend of technical rigor and domain-driven problem framing, especially for messy unstructured data. He has tackled applied challenges from counterfeit art detection with Siamese networks to anti-human-trafficking analytics, and he open-sourced tooling for large-scale multi-dataset training. Colleagues describe him as an engineer who moves models from experiment to production while keeping an eye on practical impact and interpretability.
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 UniversityBachelor's Degree Linguistics, Bachelor's Degree Linguistics at Dartmouth College
Github Skills (32)
implicit10
file-processing10
image-text10
recommender8
computer-vision8
image-processing8
feature-extraction8
machine-learning7
recommender-system7
deep-learning7
python7
jupyter-notebook6
pipeline6
pytorch6
recommendation-system6
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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