Summary
Jonlenes Castro is a Senior Software Engineer and Machine Learning architect with over a decade of experience designing and deploying production-grade AI and optimization systems across cloud and on-prem environments. He combines deep hands-on expertise in TensorFlow/PyTorch, CUDA and parallel computing with pragmatic software engineering (Docker, Kubernetes, Kafka, CI/CD) to shrink runtimes and operational costs—once cutting cloud spend by 67% and model execution time by 77%. As a former Head of Advanced Analytics, he scaled and led teams of 30 to deliver allocation optimizers and pricing models that materially improved planning speed and pricing outcomes across multiple countries. He also founded a ML consultancy to build end-to-end products, and now brings that product-to-scale perspective to his role at Meta. Comfortable translating between C-level strategy and implementation details, he pairs an MSc in Machine Learning and an MBA with a track record of measurable business impact. A less obvious strength is his cross-disciplinary background in operations research and deep learning, enabling solutions that blend mathematical programming with modern ML.
10 years of coding experience
8 years of employment as a software developer
Master of Business Administration - MBA, Master of Business Administration - MBA at Quantic School of Business and Technology
Master's degree, Machine Learning, Computer Science, 4/4, Master's degree, Machine Learning, Computer Science, 4/4 at University of Campinas
Bachelor's degree, Computer Science, 9.2/10, Bachelor's degree, Computer Science, 9.2/10 at Pontifícia Universidade Católica de Goiás
Portuguese, English