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.
9 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 (12)
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.
pythonrich-textpython3python-libraryterminal
paw-lu/invoke-dash-docset
Nov 2022 - May 2025
Contributions:11 PRs, 11 pushes, 2 branches in 2 years 5 months
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