Summary
Mateus Assis is a Machine Learning Engineer with 8 years of experience building production-ready MLOps systems in Python, specializing in Clean Architecture and deployment on Google Cloud Platform. He has practical expertise developing Scikit-Learn estimators, XGBoost models, and end-to-end ML APIs using FastAPI, MLflow and Firestore/BigQuery for industrial applications, notably in oil and gas. Mateus pairs solid engineering practices—unit testing, Python packaging, and CI-friendly design—with applied statistics and image processing using OpenCV. He has a track record of publishing applied research, mentoring teams on MLOps and feature engineering, and implementing physics-based models to modernize industrial workflows. Huawei HCIA-AI certified, he brings both academic research experience and hands-on production delivery from Rio Grande do Norte.
8 years of coding experience
5 years of employment as a software developer
Federal University of Rio Grande do Norte
técnico, mecatrônica, técnico, mecatrônica at IFRN - Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Norte
English