Summary
Felipe Garcia is a Senior Machine Learning Engineer with eight years of experience building and deploying production-grade ML systems, specializing in NLP, LLM applications, and time-series deep learning. He has shipped end-to-end solutions across Azure, Databricks, SageMaker and MLflow, turning research-grade models into APIs and monitored workflows for healthcare, finance, and hiring platforms. Felipe blends strong MLOps and data engineering skills—Spark, FastAPI, Streamlit, and containerized CI/CD—with an academic foundation from USP where he published an awarded deep learning paper. Notably, he has applied LLMs to practical problems like job classification, transaction-name translation and content moderation, improving dataset quality and user readability. Based in São Paulo, he’s pragmatic, curious, and enjoys bridging research insights with production constraints to deliver measurable impact.
8 years of coding experience
6 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at USP - Universidade de São Paulo
Nanodegree Data Science, Nanodegree Data Science at Udacity
English, Japanese, Portuguese