Deep Debroy
Engineering Leader at NVIDIA
California, United States
Summary
🤩
Rockstar🎓
Top SchoolDeep Debroy is an engineering leader with nine years of senior experience building and scaling cloud-native infrastructure, now leading multi-tenant AI Inference-as-a-Service at NVIDIA. He previously led large Kubernetes platform teams at Apple and Docker, combining deep expertise in scheduler, storage, and networking with kernel-level debugging across Windows and Linux. His career traces back through virtualization and storage roles at Cisco, Microsoft and startups, giving him rare end-to-end fluency from kernel drivers to production orchestration. An active upstream contributor, he improved DNS resilience and MX handling in the prominent Moby container project, reflecting a focus on robust, interoperable systems. Based in California, he blends hands-on engineering with people leadership to deliver efficient, scalable platforms for complex AI workloads.
9 years of coding experience
21 years of employment as a software developer
BS EECS, BS EECS at University of California, Berkeley
Github Skills (8)
container10
docker10
go10
dns10
dockers10
testing10
devops9
unit-testing9
Programming languages (10)
Github contributions (5)
moby/moby
Dec 2017 - Aug 2019
The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:12 commits, 3 PRs, 62 comments in 1 year 7 months
Contributions summary:Deep primarily focused on enhancing the DNS resolution capabilities within the project. They implemented handling of MX queries and added unit tests for DNS queries. Moreover, the user addressed a regression issue related to error handling during startup and improved the resilience of the system by retrying external DNS servers upon failure. They also made adjustments to Windows-specific test configurations.
containerscollaborative-projectgolangcontainer-ecosystemdocker
ddebroy/kubernetes
May 2018 - Mar 2020
Production-Grade Container Scheduling and Management
Contributions:2 PRs, 256 pushes, 34 branches in 1 year 9 months
containersschedulingdockergradeproduction-grade
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