Wyatt Walsh
Senior AI ML Engineer at Frame
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolWyatt Walsh is a Senior AI/ML Engineer in New York with nine years of experience building production AI/ML systems, data platforms, and developer tooling for regulated and high-stakes environments. He blends enterprise-grade engineering from JPMorgan—designing scalable, low-latency data integrations and ML-driven anomaly detection—with startup grit from founding SandLabs and shipping Web3, DeFi, and drone prototypes. Comfortable across the stack, Wyatt has architected AWS data pipelines, Python-KDB interfaces, and React/Next.js front ends while embedding LLM-driven developer tooling to accelerate SDLCs. He’s equally at home mentoring teams and securing grant-funded research, and his unofficial GitHub persona—"cookin' up some code"—reflects a pragmatic, product-focused approach to experimentation. Notably, he has moved large-scale data projects into production, from multi-million-post scrapers to trader-facing analytics, demonstrating an ability to translate research into auditable, mission-critical systems.
9 years of coding experience
4 years of employment as a software developer
High School Diploma, High School Diploma at The Hotchkiss SchoolBachelor of Science - BS Industrial Engineering and Operations Research, Bachelor of Science - BS Industrial Engineering and Operations Research at UC Berkeley College of EngineeringHigh School Diploma, High School Diploma at Bishop Union High SchoolCerro Coso Community CollegeEducational Program For Gifted Youth (EGPY) Bioengineering, Educational Program For Gifted Youth (EGPY) Bioengineering at Stanford Summer Session
English, Spanish
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (104)
spotify-api10
regression10
markdown10
shieldsio10
statistics10
probability10
data-science10
classification10
crowdsourcing10
twitter-api10
medium10
simulation10
visualization10
compilation10
machine-learning10
Programming languages (6)
Github contributions (5)
wyattowalsh/NBA-attendance-prediction
Dec 2019 - Jan 2021
Attendance prediction tool for NBA games using machine learning. Full pipeline implemented in Python from data ingestion to prediction. Attained mean absolute error of around 800 people (about 5% capacity) on test set.
Contributions:14 commits, 12 pushes, 1 branch in 1 year
data-ingestionmachine-learningpythondata-analyticsdata-science
wyattowalsh/proxywhirl
May 2025 - Jul 2026
rotating proxy system
Contributions:2 releases, 1 review, 12 PRs in 1 year 2 months
proxydatadata-extractiondataextractionproxy-checker
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