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Senior Data Scientist, Machine Learning Engineer
Experienced machine learning engineer with 8+ years developing ads and user value products - building end-to-end production ML systems from scratch, and executing innovative research to improve critical, revenue-driving deep learning models. 15+ years experience spanning machine learning (audio, vision), scientific computing, HPC, signal processing and software engineering, across DOE/DOD. Experienced mentor and teacher. Academic career teaching advanced mathematics courses (probability theory, differential equations) and publishing research in geometric mechanics.
University of Washington
Ph.D., Mathematics
January 1, 1993 – January 1, 2000
University of California, Santa Cruz
B.A., Mathematics
January 1, 1987 – January 1, 1991
University of California, Santa Cruz
Bachelor of Arts - BA, Mathematics
N/A – Present
University of Washington
Doctor of Philosophy - PhD, Mathematics
N/A – Present
University of Washington
Doctor of Philosophy - PhD, Mathematics
N/A – Present
Capital One
Senior Lead Machine Learning Engineer
June 1, 2026 – Present
San Francisco, CA · Hybrid
Meta
Software Engineer, Machine Learning
December 1, 2025 – June 1, 2026
Menlo Park, CA · Hybrid
Unity Technologies - Grow Org
Senior Machine Learning Engineer, Data Scientist
May 1, 2017 – March 1, 2025
San Francisco, CA · Hybrid
SLAC National Accelerator Laboratory
Software Engineer, Research
May 1, 2013 – May 1, 2017
Menlo Park, CA · On-site
Vista Research
Research Engineer
January 1, 2011 – March 1, 2013
Monterey, CA · On-site
United States Department of Defense
Applied Mathematician
May 1, 2005 – November 1, 2010
Fort George G. Meade, Maryland, United States · On-site
University of Michigan
Assistant Professor
January 1, 2002 – September 1, 2004
University of Washington
Senior Postdoctoral Fellow - Department of Bio-engineering
January 1, 2001 – December 1, 2001
Seattle, CA
Borland
Senior Technical Support Engineer
June 1, 1990 – June 1, 1993
Machine Learning and AI Portfolio
March 1, 2025 – Present
Self-directed projects exploring core architectures and training regimes behind modern generative AI systems. Involves hands-on experimentation in PyTorch, custom diagnostics, and in-depth technical writing. Published at: mrcartoonology.github.io. Posts include Building a Denoising Diffusion Probabilistic mode from scratch, detailing its mathematical foundations and investigating sampling instability. Implemented a transformer from scratch, demonstrated how attention head visualizations can help diagnose subtle model issues. Curiosity about how “supercalifragilisticexpialidocious” is tokenized led to wondering how a 6B LLM would behave after unlearning the word. Topics: Diffusion Models, Transformers, Model Unlearning, RoPE, Attention Visualization, Evaluation Metrics
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit for an ML Engineer role, particularly in an innovative and research-driven environment. Their personal projects highlight a passion for understanding core architectures and pushing the boundaries of AI. The diverse experience from academia, government, and multiple tech companies (Meta, Unity, Capital One) indicates adaptability and a broad perspective. The focus on solving critical business problems and leading initiatives aligns well with a results-oriented culture.
Soft Skills & Operational Fit
The candidate's extensive experience across various companies and roles, including leading teams, suggests strong collaboration and problem-solving skills. The detailed project descriptions indicate a proactive and curious approach to complex technical challenges. The long tenure at Unity Technologies (8 years) suggests stability and the ability to drive long-term projects.