Paulo Costa
Machine Learning, Search Ranking at Faire
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolPaulo Costa is a machine learning engineer with eight years of experience applying ML to search ranking and recommendation systems across major platforms including Faire, Instagram, and Meta. He combines a PhD-trained scientific mindset with production ML and infra experience, having shipped core recommendations and ads models as well as developer tooling to improve reliability and productivity. Paulo contributes to high-quality open-source projects like Textualize/rich, where he focuses on typing, bug fixes, and documentation—evidence of his attention to maintainability and developer experience. Based in the San Francisco Bay Area, he has a track record of turning messy experimental data into robust models, from discovering new nanomaterials in academic research to driving real-world product ranking improvements.
8 years of coding experience
11 years of employment as a software developer
Bachelor of Science - BS Physics, Bachelor of Science - BS Physics at California State University, StanislausData Science, Data Science at The Data IncubatorDoctor of Philosophy - PhD Physics, Doctor of Philosophy - PhD Physics at University of Nebraska-Lincoln
Github Skills (10)
typehinting10
type-checking10
python-lib10
rich-text10
python10
rich-text-editor10
rich-editor10
documentation9
terminal-emulator8
terminal-application8
Programming languages (13)
Github contributions (5)
Textualize/rich
Feb 2021 - Feb 2022
Rich is a Python library for rich text and beautiful formatting in the terminal.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:7 commits, 6 PRs, 18 comments in 11 months
Contributions summary:Paulo primarily contributed to the `rich` library by addressing typing issues and fixing potential bugs, demonstrating a focus on improving code quality and maintainability. Their work includes adding optional typing to various classes and functions within the `rich` library, fixing incorrect typing annotations (double Optional), and addressing documentation gaps. The user also improved documentation by adding missing arguments. These commits show a focused effort on enhancing the library's robustness and usability through precise code changes.
pythonprogress-bar-pythonprogress-barrich-textpretty-print
paw-lu/nbpreview
Mar 2021 - Sep 2022
A terminal viewer for Jupyter notebooks. It's like cat for ipynb files.
Contributions:2 reviews, 970 commits, 412 PRs in 1 year 6 months
ipynbpythonjupyter-notebooknotebookjupyterlab
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