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Principal Scientist
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Assessing your cultural and operational fit
Principal Scientist with SOTA research in evolving complex agents for any task. Demonstrated applications include data science, SQL generation, financial document QA, a major AGI benchmark, and protein classification. 25+ years transforming AI research into scalable, production-ready systems. Expertise in automatic machine learning, record linkage, text-to-SQL, and NLP. 15+ patents and 3000+ citations.
New York University
PhD, Computer Science
January 1, 1993 – January 1, 1999
Oberlin College
B.A., History
N/A – Present
Career Break
Personal goal pursuit
August 1, 2025 – Present
Kirkland, Washington, United States
Auger
Principal Scientist
January 1, 2025 – July 1, 2025
Bellevue, Washington, United States · On-site
Amazon
Principal Scientist
January 1, 2020 – January 1, 2024
Seattle
Amazon Web Services (AWS)
Principal Scientist
January 1, 2019 – January 1, 2020
Greater Seattle Area
Amazon Web Services (AWS)
Senior Machine Learning Scientist
January 1, 2017 – January 1, 2019
Greater Seattle Area
Amazon
Senior Machine Learning Scientist
January 1, 2014 – January 1, 2017
Greater Seattle Area
Microsoft
Principal Software Development Engineer (Bing Local)
January 1, 2013 – January 1, 2014
Bellevue, WA
Intelius
Principal Scientist and Director of Data Research
January 1, 2009 – January 1, 2012
Boies, Schiller & Flexner LLP
Independent Expert Witness
August 1, 2008 – March 1, 2009
Spock Networks
Principal Scientist
January 1, 2007 – January 1, 2009
ChoiceMaker Technologies
CEO
January 1, 1998 – January 1, 2006
RoboPhD: Evolving Diverse Complex Agents Under Tight Evaluation Budgets
August 1, 2025 – Present
If you can benchmark it, RoboPhD can optimize it. RoboPhD is an easy-to-use toolkit that evolves AI agents automatically — all you need is ~200 labeled examples, a short seed program (even one with poor accuracy), an evaluator, and a task description. This is a brand-new space, and our paper shows that RoboPhD outperforms two well-known competitors under matched budgets.
AWS Lake Formation FindMatches
June 1, 2018 – Present
AWS Lake Formation FindMatches is a new machine learning (ML) transform that enables you to match records across different datasets as well as identify and remove duplicate records, with little to no human intervention.
Cultural Fit Analysis
The candidate demonstrates a strong entrepreneurial spirit (CEO of ChoiceMaker Technologies, building RoboPhD) and a history of innovation. The diverse experience across large corporations (Amazon, Microsoft) and startups, coupled with a focus on cutting-edge AI/ML, suggests adaptability and a proactive approach to technology. The long tenure in data-intensive roles aligns well with the demands of a Big Data Engineer, indicating a strong fit for roles requiring deep technical contributions and leadership.
Soft Skills & Operational Fit
The candidate's career progression to Principal Scientist and CEO roles, along with leading significant projects, indicates strong leadership, problem-solving, and strategic thinking. The description of building and leading teams (e.g., Intelius' Data Research Group) suggests good team collaboration and mentorship capabilities. The independent expert witness role also highlights strong analytical and communication skills under pressure.