Matthew Davidow
Software Engineer at Google
New York, United States
Summary
🤩
Rockstar🎓
Top SchoolMatthew Davidow is a software engineer with six years of experience applying machine learning and Bayesian/statistical methods to real-world problems, currently at Google in New York. With a PhD in Applied Mathematics from Cornell, he blends deep probabilistic modeling expertise with practical production experience from roles at Amazon Robotics and Citi. His work spans building ML-driven stowing algorithms, fraud-detection feature engineering, and applying parallel Bayesian optimization to tune complex systems. He values intellectual honesty and embraces uncertainty, favoring principled Bayesian approaches to uncover problem structure. Driven by “ML for good,” he focuses on projects that create beneficial impact while maintaining rigorous, data-driven decision making.
7 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Applied Mathematics, Doctor of Philosophy - PhD, Applied Mathematics at Cornell University
Github Skills (24)
large-language-models10
llm10
fine-tuning10
e2e10
mistral10
gpt10
jax10
gcloud9
benchmarking9
google-cloud8
gpu8
machine-learning8
hardware8
testing8
tensorflow6
Programming languages (4)
Github contributions (5)
AI-Hypercomputer/maxtext
Apr 2023 - Jul 2026
A simple, performant, and scalable Jax LLM!
Contributions:2 releases, 1233 reviews, 326 PRs in 3 years 3 months
jaxllmlarge-language-modelsgptdeepseek
gobbleturk/FAMD
Apr 2021 - Feb 2022
Contributions:6 pushes in 11 months
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