Zachary Kimberg
Software Development Engineer at Amazon
Champaign, Illinois, United States
Summary
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Rockstar🎓
Top SchoolZachary Kimberg is a Software Development Engineer with a decade of experience building robust backend systems and ML-serving infrastructure, currently at Amazon and based in Champaign, Illinois. He combines production-grade backend development with ML engineering, contributing to projects like Apache MXNet and AWS Multi-Model Server where he improved test reliability, added worker timeouts, and strengthened request tracing. His work on the Deep Java Library shows a focus on memory management and efficient gradient handling, reflecting a practical mindset for performance and resource optimization. Comfortable in large-scale open source ecosystems, he brings a tester’s attention to detail and a developer’s drive to harden and streamline complex inference pipelines.
10 years of coding experience
1 year of employment as a software developer
University of Illinois Urbana-ChampaignParkway Central
Spanish
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (15)
memory-management10
mxnet10
javas10
deep-learning10
python10
networking10
server10
java10
test-automation10
testing9
benchmark9
benchmarking9
inference9
scala8
ai7
Programming languages (6)
Github contributions (5)
deepjavalibrary/djl
May 2019 - Dec 2022
An Engine-Agnostic Deep Learning Framework in Java
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:3 releases, 696 reviews, 348 commits in 3 years 6 months
Contributions summary:Zachary's commits primarily involve refactoring and optimization of the MXNet-based components within the DJL framework, specifically focusing on memory management and performance improvements. They removed a deprecated feature (MemoryScope), streamlined the handling of resources within the NDManager, and introduced a mechanism for tracking and accumulating gradients, with a focus on efficiency. These contributions align with development of both the back-end functionality and machine learning capabilities within the framework.
pytorchmxnetcaffe2deep-learningagnostic
apache/mxnet
Aug 2018 - Mar 2020
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:50 commits, 76 PRs, 21 pushes in 1 year 7 months
Contributions summary:Zachary primarily contributed to improving the quality and reliability of the Apache MXNet project by fixing flaky tests. These commits focused on identifying and resolving issues in existing test suites, specifically for loss functions, and expanding the test coverage of the Scala example with Resnet. The user's work involved modifying test files, indicating a focus on test maintenance and stability.
pythonschedulerdataflowmutationdata-science
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