Katie Wurman
About Katie Wurman
Katie Wurman is a Software Engineer specializing in Ocean Freight Planning at Flexport, with over 14 years of experience in machine intelligence and a strong background in AI and machine learning.
Current Position at Flexport
Katie Wurman is currently working as a Software Engineer specializing in Ocean Freight Planning at Flexport in the San Francisco Bay Area. Her role involves leading the automation of assignment planning for Flexport's global ocean freight network, which has significantly enhanced on-time performance and cost efficiency. Katie's work focuses on minimizing human errors through automation and consistently delivering high-quality production software.
Experience at Invitae
Before joining Flexport, Katie Wurman worked as an Artificial Intelligence Engineer at Invitae for three years from 2019 to 2022. In this role, she developed AI-driven solutions that advanced the company's genetic testing capabilities. Her contributions included leading projects from theoretical development to implementation as production-quality software.
Career in Machine Learning Engineering
Katie's career includes extensive experience as a Machine Learning Engineer at several organizations. From 2016 to 2018, she worked at Geli, where she was involved in creating machine learning models for energy systems. Prior to Geli, Katie spent four years at Quantcast, from 2012 to 2016, where she focused on developing machine intelligence systems tailored to online audience measurement and analytics.
Early Career and Internships
Katie Wurman began her career as a Research Engineer at AOL from 2009 to 2012, focusing on innovative research projects. She also completed internships at prominent institutions, including a brief stint at PARC in 2009 and a two-month summer internship at NASA in Air Traffic Control in 2008. Additionally, during her academic years, she gained research experience as a Research Assistant at UC Santa Cruz from 2006 to 2007.
Educational Background
Katie holds a Master of Science (M.S.) in Aeronautics/Astronautics from Stanford University, completed from 2007 to 2009. She also has a Bachelor of Arts (BA) in Mathematics from the University of California, Santa Cruz, achieved between 2005 and 2007. Her strong educational foundation has laid the groundwork for her career in software engineering and machine learning.