Mitchell Wortsman
Member Of Technical Staff at Anthropic
Greater Seattle Area United States
Summary
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Rockstar🎓
Top SchoolMitchell Wortsman is a machine learning-focused software engineer with eight years of experience bridging cutting-edge research and production systems, currently a Member of Technical Staff at Anthropic. He completed a PhD in Computer Science at the University of Washington after internships at DeepMind, Meta FAIR, and Apple, bringing strong research training into applied ML engineering. Mitchell has contributed to high-profile open-source ML tooling, notably enhancements to the open_clip implementation—adding gradient accumulation and performance fixes that support larger-scale training. His background spans academic research roles and industry internships, giving him a knack for turning novel models into reliable, scalable training pipelines. Based in the Greater Seattle Area, he combines rigorous theoretical grounding with pragmatic engineering, often focusing on training infrastructure and reproducible model development. An under-the-radar strength is his consistent involvement in both releasing and maintaining open-source releases, demonstrating attention to long-term project health as well as feature delivery.
8 years of coding experience
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of WashingtonBachelor of Science (BSc) Applied Mathematics and Computer Science, Bachelor of Science (BSc) Applied Mathematics and Computer Science at Brown University
Github Skills (10)
computer-vision10
machine-learning10
pytorch10
deep-learning10
trainings10
python10
pre-trained-model10
gradient10
model-optimization9
data-engineering9
Programming languages (9)
Github contributions (5)
mlfoundations/open_clip
Jul 2021 - Jan 2023
An open source implementation of CLIP.
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 2 reviews, 35 commits in 1 year 6 months
Contributions summary:Mitchell made several commits related to the open_clip repository, including fixes for the gather_cc data processing script and integration of gradient accumulation for training. They contributed to the training process by adding support for gradient accumulation, which is crucial for larger batch sizes. The user also released version 2.9.0 and 2.10.0 of the project and included several performance and structural improvements to the codebase.
pytorchlanguage-modelzero-shot-classificationdeep-learningclip
mitchellnw/open_clip_fork
Oct 2022 - Aug 2023
An open source implementation of CLIP.
Contributions:5 PRs, 112 pushes, 26 branches in 10 months
deep-learningclip
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