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Rafael Fabbrini has a diverse work experience spanning multiple roles in the field of technology. Starting in 2015, they worked as an Electronic Engineer Intern at the University of Portsmouth. In 2017, they joined Hands Mobile Experience as a Data Analyst, where they worked until 2019. Rafael then moved on to Semantix Brasil, where they held the position of Data Scientist from 2019 to 2021. In 2021, they transitioned to Lexter.ai as a Machine Learning Engineer, a role they held until 2022. Currently, they are employed at CarbonSpaceTech as a Machine Learning Engineer.

Rafael Fabbrini's education history begins in 2011 when they enrolled at Centro Universitário do Instituto Mauá de Tecnologia. Rafael pursued a Bachelor of Engineering (B.Eng.) degree in Mechatronics, Robotics, and Automation Engineering, and completed their studies in 2016. In 2014, they attended the University of Portsmouth and earned a Bachelor's degree in Electrical, Electronics and Communications Engineering, concluding in 2015.

In 2020, Rafael Fabbrini enrolled in the Instituto de Matemática e Estatística - Universidade de São Paulo (IME-USP) as a Special Student and pursued a Master's Degree in Statistics and Computer Science. Their studies in IME-USP lasted until 2021.

In addition to their formal education, Rafael Fabbrini obtained various certifications to expand their knowledge and skills. In 2017, they completed the Data Analyst Nanodegree program offered by Udacity. In 2018, they obtained a certification in Big Data with Spark and Hadoop ecosystem from FIAP. Later that year, they earned a Machine Learning Engineer Nanodegree from Udacity. In 2019, they completed the Deep Learning Specialization from deeplearning.ai and the Machine Learning course from Stanford University through Coursera. Rafael also acquired knowledge in Big Data with Apache Spark and Python through an Udemy course. In 2020, Rafael obtained certifications in Intro to Probability and Intro to Deep Reinforcement Learning from IME-USP. Most recently, in 2021, they completed the MLOps Specialization offered by DeepLearning.AI.