Rafael Carrascosa
Senior Principal at Mercado Libre
Cordoba, Córdoba, Argentina
Summary
🤩
Rockstar🎓
Top SchoolRafael Carrascosa is a deeply technical Senior Principal with 14 years of experience building and leading machine learning and payments systems across Latin America, currently shaping strategy at Mercado Libre from Córdoba, Argentina. He rose through hands-on ML roles into leadership—most recently Director of Machine Learning—where he blends product-oriented engineering with talent hiring to democratize commerce and payments. Rafael co-founded a startup and led ML teams at Machinalis, demonstrating entrepreneurship alongside academic roots as a former university instructor. His open-source contributions span NLP-to-query tooling and search/ML utilities, including improvements to the quepy framework and implementation of search algorithms in simpleai, highlighting both backend and algorithmic strengths. Known for tackling ambiguous, high-impact problems, he gets his kicks from projects that materially change user realities. Fluent in both research and production, he pairs rigorous code-level expertise with a track record of scaling teams and systems.
14 years of coding experience
13 years of employment as a software developer
Universidad Autónoma de MadridLicenciado en Ciencias de la Computación Computer Science, Licenciado en Ciencias de la Computación Computer Science at Universidad Nacional de CórdobaJovenes Argentinos
Spanish, English, Italian
Github Skills (11)
algorithm10
web-framework10
algorithms10
machine-learning10
nlp10
python10
natural-language-processing10
documentation9
data-structure9
data-structures9
sparql8
Programming languages (4)
Github contributions (5)
machinalis/quepy
Dec 2012 - Jan 2017
A python framework to transform natural language questions to queries in a database query language.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:51 commits, 5 PRs, 4 pushes in 4 years 1 month
Contributions summary:Rafael primarily contributed to the `quepy` framework by addressing typos and inconsistencies in the code. They fixed license mistakes and added documentation, including docstrings and cross-links within the tutorial. The user also made changes to the MQL generation component, indicating involvement in query generation and potentially in the core logic of the framework, specifically in the `quepy/mql_generation.py` file.
querypythontransformquery-languagedatabase-query
simpleai-team/simpleai
Sep 2012 - Apr 2013
simple artificial intelligence utilities
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:35 commits in 7 months
Contributions summary:Rafael contributed significantly to the `simpleai` repository, focusing on search algorithms and machine learning. They implemented beam search and bounded priority queues, and resolved merge conflicts related to changes in the `ai/methods.py` and `ai/utils.py` files. The user also added a genetic search algorithm and improved the language classification example. These changes demonstrate a focus on improving the project's core functionality related to search algorithms and the application of machine learning techniques.
artificialmachine-learningaiartificial-intelligenceintelligence
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.