Nathaniel Saul is an engineering manager and former machine learning engineer with 11 years of experience building production ML systems, MLOps pipelines, and model monitoring across companies like Stripe, New Relic, and OpenSesame. Based in Portland, he blends hands-on model development (merchant industry identification, anomaly detection) with platform work—training management, CI/CD, and data pipelines—often in AWS and modern infra like Terraform, dbt, SageMaker, and Snowflake. He has an academic foundation in topology-informed ML from his MS work, created widely used scikit-tda packages, and presented at conferences, giving him a rare combo of research depth and pragmatic engineering. Known internally as “Mr. Supportability,” he now leads teams at Stripe to improve observability and operational resilience for ML services.
11 years of coding experience
10 years of employment as a software developer
Master of Science - MS Mathematics, Master of Science - MS Mathematics at Washington State University Vancouver
Associate of Science (A.S.) Mathematics and Computer Science, Associate of Science (A.S.) Mathematics and Computer Science at Walla Walla Community College
Bachelor of Arts (B.A.) Mathematics, Bachelor of Arts (B.A.) Mathematics at University of Hawaii at Manoa
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