Nick Wilson
Machine Learning Engineer at X
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolNick Wilson is a Machine Learning Engineer with 15 years of experience building and documenting ML systems, currently based in the San Francisco Bay Area and on leave until mid/late 2026. He has a strong background spanning embedded and systems engineering to applied ML—contributing to FAA-certified avionics, mobile automated test frameworks, and conversational search during a Google internship before focusing on machine learning research and production at X. Nick is an active open-source contributor and technical writer, notably improving documentation for the widely used scikit-learn project and strengthening BigML’s Python bindings and packaging to meet community standards. His blend of low-level systems expertise (C, embedded Linux) and high-level ML practice (Python, NLP, model evaluation automation) enables him to move ideas from research prototypes into reliable production. He pairs rigorous academic training (MS Computer Science, UT Austin) with a pragmatic focus on tooling, reproducibility, and clear developer-facing documentation.
15 years of coding experience
9 years of employment as a software developer
Master of Science (MS) Computer Science, Master of Science (MS) Computer Science at The University of Texas at AustinBachelor of Science Computer Science, Bachelor of Science Computer Science at Oregon State University
Github Skills (8)
machine-learning10
api10
restructuredtext10
python10
documentation10
apim9
packaging9
data-science3
Programming languages (3)
Github contributions (5)
bigmlcom/python
Jul 2012 - Jul 2012
Python bindings for BigML.io
Role in this project:
Back-end Developer & Technical Writer
Back-end Developer & Technical WriterContributions:28 commits in 7 days
Contributions summary:Nick focused on enhancing the BigML Python bindings by implementing key features and improving the project's documentation. They added versioning information and improved the project's packaging, demonstrating an understanding of software distribution and project structure. The user also converted the README to reStructuredText, added a changelog, and expanded the documentation with a quick start guide, significantly improving the project's usability and discoverability for users.
apipythonpython-bindingsbigmlmachine-learning
scikit-learn/scikit-learn
Mar 2012 - Mar 2012
scikit-learn: machine learning in Python
Role in this project:Technical Writer
Technical WriterContributions:7 commits in 1 day
Contributions summary:Nick primarily focused on improving the project's documentation. Their contributions involved fixing minor issues in the "Contributing" guidelines, addressing doctest issues in the Gaussian Process documentation, and updating the documentation to include information on building and viewing documentation. These changes demonstrate a focus on enhancing the clarity, accuracy, and usability of the project documentation for contributors and users.
data-analysispythonstatisticsdata-sciencelearn-machine-learning
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