Cade Gordon
Member Of Technical Staff at Anthropic
Berkeley, California, United States
Summary
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Rockstar🎓
Top SchoolCade Gordon is an MS student in Computer Science at UC Berkeley and a Member of Technical Staff at Anthropic with seven years of experience building and scaling machine learning systems. He combines academic research—multiple ML projects and literature reviews at BAIR and ML@Berkeley—with hands-on engineering internships at Cohere, BigHat Biosciences, and others to move models from prototype to production. Notably, he contributed distributed training and Horovod integration to the popular open_clip repository, improving training stability and zero-shot performance. Focused on deep learning, computer vision, and applied ML, he aims to deploy models that have tangible impact, while balancing rigorous research with practical engineering. Outside of work he plays soccer as a fullback/winger, a pursuit that reflects his team-oriented, endurance-driven approach to problem solving.
7 years of coding experience
6 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at University of California, BerkeleyHigh School Diploma, High School Diploma at Stevenson High School, Lincolnshire, IL
Stackoverflow
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Github Skills (8)
pytorch10
machine-learning10
distributed-training10
deep-learning10
python10
horovod10
pre-trained-model7
computer-vision7
Programming languages (2)
Github contributions (5)
mlfoundations/open_clip
Nov 2021 - Aug 2022
An open source implementation of CLIP.
Role in this project:
ML Engineer
ML EngineerContributions:31 commits, 7 PRs, 4 pushes in 8 months
Contributions summary:Cade made several contributions focused on integrating and optimizing distributed training capabilities within the open_clip project. Key changes involved adding support for Horovod, including modifications to the training loop, parameter synchronization, and learning rate scaling. They also addressed issues related to data handling and zero-shot classification, demonstrating a focus on improving the performance and stability of the distributed training process. Further contributions included bug fixes and general improvements to the training infrastructure.
pytorchlanguage-modelzero-shot-classificationdeep-learningclip
Zasder3/Zasder3.github.io
Nov 2018 - Nov 2024
Contributions:46 pushes, 1 branch in 6 years 1 month
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