Summary
Marcos Gritti is a Founding Machine Learning Engineer with a decade of experience building production-grade AI systems that balance performance, interpretability, and scalability. Trained as a Control and Automation engineer with a master’s in Electrical Engineering, he blends deep expertise in computational intelligence—system identification, evolutionary computation, and swarm intelligence—with hands-on MLOps and cloud infrastructure work (Terraform, Kubernetes, AWS). He has led fraud-detection and risk-scoring initiatives in finance, built stateless microservices and data silos for model training, and engineered ML microservices for industrial signal processing. Comfortable across the stack, Marcos pairs high-performance simulation and low-level C work from his research days with modern data engineering (Spark, data lakes) and deployment practices. Based in the SF Bay Area, he now helps scale ambitious ML-first ventures while retaining a research-rooted approach to model calibration and real-time system behavior. An uncommon strength is his ability to translate control-theory and system-identification insights into robust, auditable ML pipelines for regulated, decision-critical environments.
10 years of coding experience
8 years of employment as a software developer
Programa de Pós Graduação em Engenharia Elétrica (PPGEE) Sistemas Eletrônicos, Programa de Pós Graduação em Engenharia Elétrica (PPGEE) Sistemas Eletrônicos at Universidade Federal do Paraná
Pontifical Catholic University of Paraná
English, Spanish