About

Nathaniel Saul is a highly skilled Machine Learning Engineer with extensive experience in model evaluation and monitoring, data pipelines, training management, and CI/CD. He is currently working at Stripe, where he is responsible for building scalable systems that can be iterated on quickly. Nathaniel's specialty lies in wrangling all the moving pieces required to get ML in front of the user. Before joining Stripe, Nathaniel worked as a Senior Machine Learning Engineer at Opensesame, where he focused on building search and recommendation systems. He also has experience in MLOps in the AWS ecosystem and has worked with technologies such as Python, Terraform, dbt, Github Actions, Lambda, Sagemaker, Snowflake, Step Functions, API Gateway, Flask, and Huggingface Transformers. Nathaniel holds a Master of Science degree in Mathematics from Washington State University Vancouver and a Bachelor of Arts degree in Mathematics from the University of Hawaii at Manoa. He also has an Associate of Science degree in Mathematics and Computer Science from Walla Walla Community College and a High School Diploma in Applied Sciences from Pullman High School. Nathaniel's technical expertise includes ML, CI/CD, AWS, recommendation systems, Sagemaker, Snowflake, Terraform, Python, search, and Flask. With almost 5 years of relevant experience, Nathaniel is a highly skilled professional who is dedicated to building scalable and efficient ML systems.