Adam Deconinck
Senior Manager at NVIDIA
Denver, Colorado, United States
Summary
🤩
Rockstar🎓
Top SchoolAdam Deconinck is a senior manager and systems engineer with 14 years of experience designing, deploying, and architecting HPC and AI compute systems across datacenter infrastructure through systems software. Currently leading a team at NVIDIA, he has driven product and solutions architecture for accelerated computing, including hands-on work building GPU clusters and improving CI/CD for notable open-source tooling like NVIDIA/deepops. His background spans production engineering at Facebook, supercomputer deployment at Los Alamos National Laboratory, and early HPC systems engineering, giving him deep expertise in scalable, high-performance distributed systems. He blends strategic leadership with practical engineering—comfortable both in customer-facing architecture roles and low-level deployment automation. Based in Denver, he pairs a physics and materials science academic foundation with a knack for smoothing complex operational workflows. On a lighter note, he’s the sort of engineer who jokes about arguing with cats or supercomputers depending on the day, hinting at a pragmatic but curious personality.
14 years of coding experience
16 years of employment as a software developer
B.S., Physics, B.S., Physics at Michigan Technological UniversityMS, Materials Science and Engineering, MS, Materials Science and Engineering at University of Illinois Urbana-Champaign
Stackoverflow
230reputation
11kreached
4answers
4questions
Github Skills (22)
kubernetes10
docker10
dockers10
cicd10
kubernetes-pods10
ansible10
ansible-galaxy10
bash9
infrastructure-as-code9
ingress8
containerization8
metallb8
shared-memory6
container-registry6
containerd6
Programming languages (9)
Github contributions (5)
NVIDIA/deepops
Feb 2019 - Dec 2022
Tools for building GPU clusters
Role in this project:
DevOps Engineer
DevOps EngineerContributions:3 releases, 207 reviews, 945 commits in 3 years 10 months
Contributions summary:Adam focused on enhancing the infrastructure and deployment aspects of the `nvidia/deepops` repository, which includes tools for building GPU clusters. Their commits involved configuring the virtual cluster setup, including Kubernetes, by modifying scripts related to cluster creation, environment setup, and ingress configuration. They also improved the CI/CD process by adding linting checks and streamlining deployment steps. They also made changes to the local container registry.
gpuclusters
ajdecon/hpc-chef
Jan 2012 - Oct 2012
Contributions:53 commits in 10 months
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