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Simplifying Retrieval + AI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Building the next generation of retrieval + AI systems. Get in touch! I've been working on model inference, retrieval and ranking algorithms, model deployment and monitoring, and model training pipelines. I've worked deeply across search infrastructure, ranking, and experimentation.
Loyola University Chicago
Master of Science (M.S.), Statistics
January 1, 2013 – January 1, 2014
Grand Valley State University
Bachelors, Advertising
January 1, 2006 – January 1, 2009
Hex
Staff Software Engineer
June 1, 2026 – Present
Seattle, Washington, United States
Figma
Staff Software Engineer
January 1, 2025 – June 1, 2026
Seattle, Washington, United States
DeployQL
Founder, CEO
August 1, 2023 – January 1, 2025
Greater Seattle Area · On-site
Dropbox
Machine Learning Engineer
February 1, 2019 – August 1, 2023
Interactions Digital Roots
AI Engineer
July 1, 2017 – February 1, 2019
Greater Seattle Area
PitchBook Data
Machine Learning Engineer
October 1, 2016 – July 1, 2017
Greater Seattle Area
Digital Roots
Data Scientist
January 1, 2015 – August 1, 2016
Greater Seattle Area
Cultural Fit Analysis
The candidate has a diverse background, including founding a company and working at various tech companies from startups to large enterprises (Figma, Dropbox). Their experience spans different aspects of ML/AI, from research and development to productionization and system design. This breadth of experience suggests adaptability and a willingness to tackle varied challenges, which could contribute positively to cultural fit. The target role of 'NLP Engineer' aligns well with their extensive experience in natural language understanding, search, and LLMs.
Soft Skills & Operational Fit
The candidate's resume indicates leadership experience (Founder, CEO at DeployQL; leading cross-functional projects at Dropbox; organizing sprints at Interactions Digital Roots) and a history of driving product roadmap decisions through technical work. This suggests strong operational fit and leadership potential. The descriptions also imply problem-solving and innovation, such as developing a novel vector database and building state-of-the-art deep learning applications.