Cryssi Volzka
ZCX Developer at IBM
Rochester, Minnesota, United States
Summary
🤩
Rockstar🎓
Top SchoolCryssi Volzka is a seasoned software engineer and product-focused developer with a decade of experience delivering enterprise-grade Cloud and AI features at IBM, currently working as a zCX Developer. She has led cross-functional teams and productization efforts—bridging IBM Z development with research—to ship Day 0 support for on-chip AI accelerators and multiple production releases. Her hands-on background ranges from Kubernetes device plugins and gRPC streaming to CI/CD and secure container specifications, demonstrating a blend of systems, DevOps, and ML-inference expertise. An active contributor to prominent open-source ML projects like ONNX and ONNX-MLIR, she has helped streamline releases and improve build/test infrastructure, highlighting a knack for release engineering and maintainability. Colleagues describe her as organized, customer-focused, and mindful of the human side of engineering, consistently prioritizing clear handoffs and usable end-user experiences.
10 years of coding experience
10 years of employment as a software developer
Computer Science, Computer Science at University of Wisconsin-Marathon CountyBachelor's Degree, Computer Science, Bachelor's Degree, Computer Science at University of Wisconsin-Eau Claire
English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (13)
release-management10
machine-learning10
onnx10
protobuffer10
protobuf10
java9
python9
cprogramming-language9
c-language9
deep-learning9
javas9
build-automation8
build-system7
Programming languages (8)
Github contributions (5)
onnx/onnx-mlir
Jan 2022 - Dec 2022
Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure
Role in this project:
Back-end Developer
Back-end DeveloperContributions:9 releases, 102 reviews, 11 commits in 11 months
Contributions summary:Cryssi primarily contributed to the project by modifying existing code and updating dependencies. Their work focused on refactoring code for clarity, switching URLs to use the main branch, and fixing typos. They also updated the protobuf version and adjusted file permissions for Java-related components. The changes suggest a focus on code maintainability, build processes, and compatibility.
pytorchrepresentationdeep-learningmlironnx-models
onnx/onnx
Jan 2022 - Jan 2022
Open standard for machine learning interoperability
Role in this project:ML Engineer
ML EngineerContributions:3 releases, 16 reviews, 1 commit in 1 day
Contributions summary:Cryssi primarily contributed to the ONNX repository by modifying code related to preparing for and cutting releases, as well as bumping the ONNX operator set. Their work included updating version numbers, modifying schema definitions, and preparing testing infrastructure, showcasing involvement in release management. The user also addressed code quality and build issues by fixing broken URLs and improving build processes.
pytorchmxnetdeep-learninginteroperabilitymachine-learning
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