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Chief Science Officer at EdgeRunner AI
Passionate about building state-of-the-art AI for the American people. ‣ Chief Science Officer at EdgeRunner AI ‣ Lead author of plan for first major LLM program at Amazon; founding member of first modeling team ‣ Hands-on foundation model builder; data, pretraining, posttraining, eval ‣ Owner of production ML models used by millions while in Amazon Alexa ‣ People leader for sales, BI, and vendor negotiations in Amazon Retail ‣ Physicist and new technology builder for countering WMD at DTRA ‣ Former Air Force officer (Captain) ‣ Commandant’s awardee for best masters thesis at AFIT (#1/242) ‣ Academy Scholar at US Air Force Academy (top 5%) Soli Deo Gloria
U.S. Air Force Institute of Technology
Master of Science - MS, Nuclear Physics
N/A – Present
United States Air Force Academy
Bachelor of Science - BS, Physics
N/A – Present
EdgeRunner AI
Chief Science Officer
August 1, 2025 – Present
Colorado, United States
Amazon
Principal, Applied Scientist
April 1, 2023 – August 1, 2025
Amazon
Senior Applied Research Scientist
February 1, 2020 – April 1, 2023
Amazon
Manager, Research Science - Alexa
February 1, 2017 – February 1, 2020
Amazon
Manager, Product Management - Retail
June 1, 2015 – February 1, 2017
Defense Threat Reduction Agency
Nuclear Physicist, Air Force Captain
March 1, 2012 – June 1, 2015
Washington D.C. Metro Area
Air Force Institute of Technology
Nuclear Physicist, Air Force Lieutenant
May 1, 2010 – March 1, 2012
United States Air Force Academy
Flight Commander, Payload Team Lead, Cadet
June 1, 2006 – May 1, 2010
Science and Technology Manager Level 1
Defense Acquisition University
June 24, 2026 – Present
Program Management Level 1
Defense Acquisition University
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's extensive experience at Amazon, a fast-paced, innovation-driven environment, suggests a strong cultural fit for similar organizations. Their involvement in co-founding the Alexa LLM org, leading tiger teams, and driving significant technical advancements indicates a proactive, ownership-oriented mindset. The diversity of roles, from technical leadership in ML to product management and even military science, shows adaptability and a broad perspective, which can be highly beneficial for complex ML engineering challenges.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, project management, and team-building skills through their various roles at Amazon and the Defense Threat Reduction Agency. Their ability to coordinate large teams (900+ contributors for Nova Technical Report), secure funding, and lead workshops indicates excellent communication and collaboration. The progression through management and principal roles suggests strong operational fit for senior leadership within an ML engineering context.