Makoto Yui
Senior Principal Software Engineer at Treasure Data
Chiyoda, Japan
Summary
🤩
Rockstar🎓
Top SchoolMakoto Yui is a Senior Principal Software Engineer with 13 years of experience building large-scale machine learning and data processing systems, currently leading the AutoML effort at Treasure Data in Tokyo. He designed and productized Treasure Automl from scratch, organized and grew the ML team, and engineered an auto-scaling container platform and workflow/container integrations for production ML services. A veteran open-source contributor and initial developer of Apache Hivemall, he has hands-on expertise implementing ML algorithms, feature-engineering UDFs, and fixing core optimizer bugs that improved model accuracy. His background spans research and industry—from distributed data processing research at AIST and visiting roles in Europe to deploying ML-as-a-Service used by Fortune 500 customers across diverse industries. Comfortable bridging research and product, he pairs a PhD-level understanding of systems with practical skills in shipping resilient, scalable ML infrastructure. Colleagues describe him as a technical lead who both architects platforms and still dives into low-level algorithmic fixes.
12 years of coding experience
16 years of employment as a software developer
Ph.D, Computer Science, Ph.D, Computer Science at Nara Institute of Science and TechnologyBachelor's Degree, Computer Science, Bachelor's Degree, Computer Science at Shibaura Institute of Technology, Japan
English, Japanese
Stackoverflow
296reputation
647kreached
10answers
0questions
Github Skills (14)
javas10
machine-learning10
feature-engineering10
java10
data-science9
big-data9
user-defined-function6
lambda6
hive6
btree6
rank6
hadoop6
on-disk6
tree6
Programming languages (6)
Github contributions (5)
myui/hivemall
Sep 2013 - Dec 2016
Scalable machine learning library for Apache Hive/Spark/Pig
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:18 releases, 1585 commits, 260 PRs in 3 years 2 months
Contributions summary:Makoto focused on implementing new machine learning classifier models, namely adagrad_rda, and tools like convert_label() UDF. They also addressed a bug in AdaGrad, potentially improving the accuracy of the machine learning models. Additionally, the user introduced enhancements like the add_feature_index and other feature engineering UDFs for improving the process of preparing feature vectors.
pigscalableapachemachine-learningbig-data
myui/btree4j
Dec 2017 - Aug 2020
Disk-based B+-tree written in Pure Java
Contributions:49 commits, 4 PRs, 46 pushes in 2 years 8 months
cpppure-javadiskdisk-basedb-tree
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