Summary
Diego Sánchez is a Machine Learning Engineer with 10+ years of cross-functional experience spanning QA, data engineering, backend systems, and production ML, currently leading business integrity efforts at Meta. He has repeatedly delivered high-impact solutions—ranging from federated learning and on-device LLM fine-tuning to reinforcement-learning and optimization-based detection systems—that collectively prevented hundreds of millions in revenue leakage and enabled tens of millions in business value. Comfortable across Python, TypeScript, Java, Go and cloud platforms (GCP/AWS), he architects scalable batch and streaming pipelines using Beam, DataFlow, Airflow and modern infra like Terraform. Diego pairs research rigor (MSc in Computer Science) and academic teaching experience with hands-on product migrations and system rewrites that improved reliability, observability, and developer productivity. He is an active open-source author (TRUNAJOD, py-logic) and an applied NLP practitioner who has built novelty solutions such as gibberish-email detectors and federated CV/next-word models. Based in Seattle, he combines practical engineering leadership with a penchant for turning NLP and ML research into production-grade defenses against fraud and compromise.
10 years of coding experience
5 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at Universidad de Concepción
AI Engineer using Microsoft Azure Inteligencia artificial, AI Engineer using Microsoft Azure Inteligencia artificial at Udacity
Spanish, English