Júlio Guedes

Developed and maintained critical infrastructure applications for the IO Apps team, leading a zero-downtime Redis cluster migration that saved an estimated $71,000 annually and drove Black Friday readiness that achieved 100% SLA while reducing operational costs by $70,000 year-over-year.

Built end-to-end personalized user feeds with low-latency, highly reliable systems; implemented in-app metrics and dashboards to improve observability and optimized data pipelines to reduce execution time by over 70%.

Promoted from Data Science intern to lead a team of three to research and deploy real-time ML models in a microservice environment, improving customer service efficiency with data-driven solutions.

Promoted from intern to lead a team of three to develop and deploy real-time ML microservices for customer service efficiency, delivering production ML solutions using TensorFlow and Scikit-learn.

Implemented features for a large-scale web system for law enforcement and refactored the codebase to improve developer experience, code review efficiency, and feature integration.

Master's research on performance and explainability improvements through transfer learning and pre‑training; coursework focused on web development, data science, and machine learning with interest in NLP and recommender systems.

Master's research on performance and explainability improvement through transfer learning and pre‑training; coursework focused on web development, data science, and machine learning with interest in NLP and recommender systems.