Josh Gardner
Member Of Technical Staff at Anthropic
Seattle, Washington, United States
Summary
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Rockstar🎓
Top SchoolJosh Gardner is a research-driven software engineer with 11 years of experience bridging applied machine learning, foundation models, and production engineering across top AI labs and tech companies. He has held research and engineering roles at Anthropic, Apple, Google DeepMind (Magenta), Spotify, and Google, bringing a blend of academic rigor from a PhD in Computer Science and practical product experience. His background spans music and creativity-focused ML research, applied statistics, and information retrieval, enabling him to move experimental models toward real-world deployment. Earlier work in education analytics and teaching reflects a strong grounding in data-driven decision making and clear communication of complex ideas. Based in Seattle, he pairs deep research instincts with hands-on implementation skills, often working at the intersection of model development and scalable systems. A less obvious thread in his career is a consistent focus on human-centered ML applications—from learning analytics to creative tools—rather than purely algorithmic novelty.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of WashingtonMaster of Science - MS Applied Statistics, Master of Science - MS Applied Statistics at University of Michigan - Rackham Graduate SchoolBA with High Distinction and Highest Honors Philosophy, BA with High Distinction and Highest Honors Philosophy at University of MichiganMaster of Science in Information Information Analysis and Retrieval, Master of Science in Information Information Analysis and Retrieval at University of Michigan - School of Information
Github Skills (166)
language-model10
python10
attention-mechanism10
stylegan10
datasets10
deep-learning10
tabular10
flamingo10
optimization10
multimodal10
ml10
audio10
neural-network10
computer-vision10
nlp10
Programming languages (10)
Github contributions (5)
jpgard/dro
Feb 2020 - Jul 2020
Experiments in distributionally-robust optimization
Contributions:52 PRs, 281 pushes, 55 branches in 5 months
optimizationrobust-optimizationoptuna
jpgard/characterizing-rd-of-dp
Dec 2020 - Dec 2021
Code for "Characterizing the Representation Disparity of Differential Privacy"
Contributions:19 PRs, 499 pushes, 23 branches in 1 year
representationprivacydifferential-privacydisparitydifferential
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