Sam Skalicky
Staff Software Engineer - Perception at Rivian
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSam Skalicky is a Staff Software Engineer specializing in perception systems with nine years of industry experience and a PhD in Computing & Information Sciences from RIT. He has a strong track record building and optimizing deep learning frameworks and compilers across Amazon (MXNet, TVM, SageMaker Neo, Elastic Inference, Annapurna/AWS Neuron) and IBM’s inference accelerator stack, now applying that expertise to perception at Rivian. Sam is an active open-source contributor to high-profile projects like Apache MXNet, where he improved reliability by fixing activation bugs and adding operator tests, reflecting a focus on robust, production-grade ML infrastructure. His background spans reconfigurable computing and embedded systems from roles at Xilinx and ISI, giving him rare cross-stack fluency from hardware acceleration to PyTorch integrations. Outside core engineering he mentors robotics students and brings multilingual curiosity—intermediate Korean and a liberal arts concentration in Japanese—into collaborative, global teams.
9 years of coding experience
10 years of employment as a software developer
PhD Computing & Information Sciences, PhD Computing & Information Sciences at Rochester Institute of TechnologyAssociate of Science - AS Engineering, Associate of Science - AS Engineering at Monroe Community College
English, Korean, Japanese
Github Skills (9)
unit-testing10
mxnet10
machine-learning10
deep-learning10
python10
testing10
cprogramming-language9
c-language9
cuda8
Programming languages (5)
Github contributions (5)
apache/mxnet
Jul 2018 - Nov 2021
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:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:3 releases, 157 reviews, 77 commits in 3 years 4 months
Contributions summary:Sam contributed to the Apache MXNet project by fixing bugs, improving existing features, and adding new tests. They corrected errors in the softsign activation function and optimized size checks for the MKLDNN library. The user also implemented new tests for the pooling operator, spatial transformer, dropout, and smooth L1 loss. Their work demonstrates a focus on improving the reliability and functionality of the deep learning framework.
pythonschedulerdataflowmutationdata-science
samskalicky/incubator-mxnet
Apr 2019 - Apr 2021
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Contributions:322 commits, 2 PRs, 503 pushes in 2 years
pythonschedulerdataflowmutationdata-science
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