Motoki Wu
Applied AI Engineer at Salient
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolMotoki Wu is an Applied AI Engineer in San Francisco with 12 years of experience building NLP and machine learning systems that move from research to production. He has held technical and leadership roles across startups and product teams—co-founding data-driven ventures, leading data science at Chegg, and developing ML products at Cresta—now focused on augmenting workflows with LLMs. His open-source work includes improving test and QA infrastructure for the widely used spaCy NLP library, reflecting a pragmatic emphasis on reliability and reproducibility. Trained in statistics and quantitative ecology at UC Davis and the University of Washington, he brings rigorous modeling instincts to practical engineering problems. Known for the motto “replacing myself with LLMs” and a reluctance to finetune out of the box, he favors efficient, maintainable automation over unnecessary complexity.
13 years of coding experience
12 years of employment as a software developer
PhD (Unfinished) Quantitative Ecology & Resource Management, PhD (Unfinished) Quantitative Ecology & Resource Management at University of WashingtonBachelor of Science (BS) Statistics Applied Mathematics (double major), Bachelor of Science (BS) Statistics Applied Mathematics (double major) at University of California, DavisAssociate of Arts (AA) General Studies, Associate of Arts (AA) General Studies at Diablo Valley College
English, Japanese
Stackoverflow
336reputation
17kreached
3answers
8questions
Github Skills (17)
pytest10
python10
testing10
natural-language-processing9
nlp9
ai8
artificial-intelligence8
machine-learning7
command-line-interface7
fileio6
deep-learning6
amazon-ec26
tensorflow6
gensim6
amazon-web-services6
Programming languages (11)
Github contributions (5)
explosion/spaCy
Nov 2017 - Jun 2019
💫 Industrial-strength Natural Language Processing (NLP) in Python
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:7 commits, 6 PRs, 22 comments in 1 year 7 months
Contributions summary:Motoki primarily focused on improving the testing infrastructure of the spaCy library. Their contributions included adding new tests to address specific issues related to noun chunk iterators and NER functionality. Furthermore, they incorporated tests to validate functionality added to the `spacy pretrain` CLI tool, specifically the `--save-every` and resume logic options. These additions enhance the test coverage and overall reliability of the library.
natural-language-processingpythondata-sciencemachine-learningcython
tokestermw/text-gan-tensorflow
Mar 2017 - Apr 2017
TensorFlow GAN implementation using Gumbel Softmax
Contributions:42 commits, 26 pushes, 1 branch in 12 days
softmaxtensorflowartificial-intelligencetensorflow-gangumbel-softmax
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