Richard Izzo
Senior Software Engineer - AI Infrastructure Services at NVIDIA
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolRichard Izzo is a senior software engineer specializing in AI infrastructure, currently building scalable services at NVIDIA after guiding platform development at Lightning AI. With nine years of experience spanning startup founding to enterprise engineering, he co-created RedisAI and Hangar as CTO of tensorwerk—projects that delivered industry-leading inference performance and tensor-native data versioning adopted by organizations like CERN. He combines deep ML/DL systems knowledge with hands-on backend and cloud DevOps expertise, contributing to high-profile open-source work such as PyTorch Lightning’s multi-GPU/multi-TPU tooling and CI/CD improvements. Richard’s background in biomedical engineering and a PhD-focused trajectory gives him a strong applied-research mindset that he uses to bridge rigorous experimentation and production-grade systems. He’s known for squeezing orders-of-magnitude performance gains out of serving and data pipelines while keeping developer ergonomics and reproducibility front and center. Based in New York, he thrives at the intersection of research, product, and scalable infrastructure.
9 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Biomedical/Medical Engineering, Doctor of Philosophy (Ph.D.) Biomedical/Medical Engineering at University at Buffalo
Github Skills (15)
cloud-infrastructure10
cloud-services10
cloud-computing10
python10
back-end-development10
devops10
cicd10
dockers9
machine-learning9
docker9
pytorch9
kubernetes8
kubernetes-pods8
data-science8
aws8
Programming languages (14)
Github contributions (5)
Lightning-AI/pytorch-lightning
Aug 2022 - Jan 2023
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:55 reviews, 22 commits, 31 PRs in 5 months
Contributions summary:Richard primarily contributed to the backend infrastructure and cloud deployment aspects of the project. They implemented cloud-related features, including drive specifications and mount functionalities, indicating a focus on cloud integration. The user addressed CI/CD issues, such as reducing load in testing, and made modifications to command execution within the application. Additionally, the user addressed build and test errors, and refactored code.
pythonheadachespytorch-modelsdata-sciencehandling
tensorwerk/hangar-py
Apr 2019 - Sep 2020
Hangar is version control for tensor data. Commit, branch, merge, revert, and collaborate in the data-defined software era.
Contributions:12 releases, 550 commits, 262 PRs in 1 year 4 months
version-controlmerge-branchdefinedcollaboratemachine-learning
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