Brandon Tuttle

Solution Architect Manager at NVIDIA

Ann Arbor, Michigan, United States
email-iconphone-icongithub-logolinkedin-logotwitter-logostackoverflow-logofacebook-logo
Join Prog.AI to see contacts
email-iconphone-icongithub-logolinkedin-logotwitter-logostackoverflow-logofacebook-logo
Join Prog.AI to see contacts

Summary

👤
Senior
🎓
Top School
Brandon Tuttle is a Solution Architect Manager at NVIDIA with eight years of experience turning AI experiments into production-grade systems. He leads full-stack deployment efforts—architecture, MLOps orchestration, and application optimization—helping teams ship performant GPU-accelerated solutions. Previously a senior ML engineer and program leader at Domino’s, he built production NLP, forecasting, and recommendation pipelines and championed containerized, scalable deployments with Docker and Kubernetes. An active contributor to NVIDIA’s deepops tooling, he’s hands-on with automating GPU cluster deployments and local registry workflows. Based in Ann Arbor, he blends enterprise consulting roots in healthcare analytics with practical home-lab administration, making him as comfortable sketching architectures as debugging kubectl commands at 2 a.m.
code8 years of coding experience
job8 years of employment as a software developer
bookBachelor of Science (B.S.), Bachelor of Science (B.S.) at University of Michigan
stackoverflow-logo

Stackoverflow

Stats
1reputation
0reached
0answers
0questions
github-logo-circle

Github Skills (10)

kubernetes10
docker10
dockers10
kubernetes-pods10
bash9
yaml8
cicd8
githubaction-workflow7
github-ci7
deep-learning6

Programming languages (6)

ShellRC++GoJupyter NotebookPython

Github contributions (5)

github-logo-circle
NVIDIA/deepops

Dec 2021 - Jul 2022

Tools for building GPU clusters
Role in this project:
userDevOps Engineer
Contributions:42 commits, 1 PR, 4 comments in 6 months
Contributions summary:Brandon primarily focused on developing and maintaining deployment scripts for deep learning examples within a Kubernetes environment. Their contributions involved creating, deleting, and configuring services using `kubectl` and `docker-compose`. They also updated deployment scripts, added support for pushing images to a local registry, and made improvements to the overall deployment process. The user's work centered on automating the deployment and management of deep learning workloads on GPU clusters.
gpuclusters
Contributions:16 commits, 14 pushes, 1 branch in 2 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.
Request Free Trial
Brandon Tuttle - Solution Architect Manager at NVIDIA