Felipe Hummel
IA Educação at ?
São Paulo, Brazil
Summary
👤
Senior🎓
Top SchoolFelipe Hummel is a seasoned software engineer with 16 years of experience building scalable products across the full stack, from distributed crawlers and ElasticSearch-backed search to React UIs and AI-driven features. He has deep functional-programming expertise (7 years Clojure, 4 years Scala) and a track record of turning prototypes into production—examples include NuPay at Nubank, a QR-based payment system, and "Talk with the Book" and embeddings-driven recommendations at Árvore. Felipe has led teams as an engineering manager and tech lead, scaling a squad to serve millions of customers and introducing architecture and release practices like modular monoliths and feature toggles. He combines hands-on backend work (including a text-summarization backend on GitHub) with product sensibility, often shipping tools that tangibly improve developer productivity and content moderation. Based in São Paulo, he blends startup grit with enterprise-scale engineering and a curiosity for emerging AI integrations.
16 years of coding experience
14 years of employment as a software developer
Master Information Retrieval Databases, Master Information Retrieval Databases at Universidade Federal do Amazonas
English, Portuguese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (13)
imp10
object-oriented-programming10
traits10
implement10
scala10
dependency-injection9
guice9
test-integration8
unit-testing8
integration-testing8
testing8
unit-test8
test-unit8
Programming languages (6)
Github contributions (5)
MojoJolo/textteaser
Oct 2013 - Oct 2013
TextTeaser is an automatic summarization algorithm.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 commits in 1 day
Contributions summary:Felipe primarily contributed to the back-end logic of the text summarization project. They refactored the code by introducing a `KeywordService` trait and implemented a `DummyKeywordService` for testing purposes. They also created a `Summary` object, which streamlined the output format. Additionally, the user added a REPL for testing the summarization functionality and modified the main application to accommodate the new `Summary` object.
nlppythonsummarization-algorithmmachine-learningtextteaser
felipehummel/TinySearchEngine
Jun 2011 - Jan 2016
Contributions:22 commits, 5 pushes in 4 years 7 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.