Principal Deep Learning Performance Engineer - Training At Scale at NVIDIA
Eindhoven Area Netherlands
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Summary
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Jeremi Piotrowski is a Principal Deep Learning Performance Engineer with 11 years of experience building and optimizing distributed systems, Linux stacks, and cloud-native infrastructure for large-scale training workloads. Currently at NVIDIA working on MLPerf Training, he previously led low-level OS, hypervisor and container efforts at Microsoft—contributing to AKS, KVM/Hyper-V optimizations, NVIDIA GPU Operator support, and Kata/Confidential Containers. His background spans SoC bring-up and Linux kernel driver development to secure HSM architecture and compliance, giving him a rare blend of hardware-near engineering and cloud-scale performance tuning. An active contributor to open source CI/CD and Kata Containers workflows, he has hands-on experience adapting complex build and test pipelines for ephemeral VM/container environments. Based in Eindhoven and grounded in physics (MSc), he combines rigorous analytical training with practical systems engineering to squeeze performance and security out of heterogeneous compute stacks.
11 years of coding experience
10 years of employment as a software developer
Physics, Physics at Heidelberg University
Master of Science - MS, Physics, Master of Science - MS, Physics at AGH University of Krakow
Kata Containers is an open source project and community working to build a standard implementation of lightweight Virtual Machines (VMs) that feel and perform like containers, but provide the workload isolation and security advantages of VMs. https://katacontainers.io/
Role in this project:
DevOps Engineer & System Architect
Contributions:199 reviews, 71 PRs, 20 pushes in 2 years 1 month
Contributions summary:Jeremi primarily focused on improving the build and deployment processes for Kata Containers. They implemented changes to the CI/CD pipeline, specifically within the GitHub Actions workflow, including creating a skeleton for a VFIO job and adapting test setups for the new environment. They also addressed issues with caching and artifact ownership during builds. Their work involved modifying scripts for image creation, system configuration, and test execution to ensure the system worked correctly in CI and deployment.
Contributions:76 pushes, 20 branches in 6 years 5 months
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Jeremi Piotrowski - Principal Deep Learning Performance Engineer - Training At Scale at NVIDIA