Summary
Cayo Da Silva Neves is a Machine Learning Engineer with a decade of experience building scalable data-driven systems and production ML lifecycles. He blends hands-on MLOps — orchestrating Airflow workflows, Spark processing, and Iceberg data lakes — with software engineering practices in Docker and Kubernetes to deliver high-availability model execution services. Previously he architected resilient, large-scale backend systems for financial messaging and omnichannel e-commerce, using Node.js, Go, Python and cloud-native AWS services. Comfortable across the full stack, he has shipped mobile, web, and backend platforms while also owning infrastructure as code and asynchronous architectures. Based in Goiás, Brazil, he pairs formal study in Data Science and ML with practical experience bridging data engineering and ML in mission-critical environments. He’s notable for shifting between fast product delivery and hardened production operations, turning complex pipelines into repeatable, scalable services.
10 years of coding experience
6 years of employment as a software developer
Bacharelado em Sistemas de Informação Informática, Bacharelado em Sistemas de Informação Informática at Instituto Federal de Goiás (IFG)
Especialização em Ciência de Dados e Machine Learning Informática, Especialização em Ciência de Dados e Machine Learning Informática at Pontifícia Universidade Católica de Campinas
Spanish, Portuguese, English