Marlesson Santana
Staff Machine Learning Engineer at Jusbrasil
Bahia, Brazil
Summary
👤
Senior🎓
Top SchoolMarlesson Santana is a Staff Machine Learning Engineer and PhD-trained computer scientist with 11+ years building scalable ML systems across gaming, fintech, and marketplace domains. He combines deep research in recommender systems and contextual bandits with hands-on engineering—designing end-to-end pipelines, large-scale Spark/Databricks data flows, and production deployment on cloud platforms. As a former research lead and educator, he has mentored 200+ students and peers and translated academic ideas into open-source tools and industry solutions for companies like Wildlife Studios, Trustly, and Birdie. His background spans both NLP and probabilistic modeling, with notable work applying reinforcement-learning approaches to marketplace recommendations. Based in Bahia, Brazil, he brings a rare blend of theoretical rigor and product-focused delivery, often bridging research prototypes into monitored, real-world ML services.
11 years of coding experience
14 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Universidade Federal de GoiásMaster's degree Computational Modeling in Science and Technology, Master's degree Computational Modeling in Science and Technology at Universidade Estadual de Santa Cruz
English, Portuguese
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (41)
autoencoder10
imdb9
react8
flask8
collaborative-filtering8
recommendation-system7
convolutional-neural-networks7
analytics7
keras7
python7
windows-subsystem-for-linux6
crawler6
activerecord6
scrapy6
data-visualization6
Programming languages (5)
Github contributions (5)
deeplearningbrasil/mars-gym
Jul 2019 - Nov 2021
Contributions:365 commits, 9 pushes, 2 branches in 2 years 5 months
marlesson/recsys_autoencoders
Feb 2019 - Nov 2019
This project implements different Deep Autoencoder for Collaborative Filtering for Recommendation Systems in Keras
Contributions:14 commits, 6 pushes, 1 branch in 9 months
autoencodercollaborative-filteringkerasrecommendation-systemdeep-learning
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