Summary
Joel Pires is a researcher and software engineer based in Bahia, Brazil, with nine years of experience building recommender systems, smart-home automation models, and ML-driven interaction layers. Currently at Universidade Federal da Bahia, he focuses on reliability, calibration, and performance of recommendation engines and integrates large language models for task automation and user interaction. His background spans industry roles including data science at Ford and software engineering in the federal judiciary, giving him hands-on experience deploying ML in production contexts. Trained in computer engineering and software engineering with a master's in computer science underway, he combines academic rigor with practical system design and architecture skills. Colleagues describe him as proactive, continually learning, and drawn to novel problems at the intersection of AI and everyday automation.
9 years of coding experience
3 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at Universidade Federal da Bahia
Bacharelado em Engenharia, Computer Engineering, Bacharelado em Engenharia, Computer Engineering at UFRB - Universidade Federal do Recôncavo da Bahia
English, Portuguese