Linnea Huxford
Principal Software Architect Tech Lead Team Lead Technical Product Owner at Alley
Portland, Oregon Metropolitan Area United States
Summary
🤩
Rockstar🎓
Top SchoolLinnea Huxford is a Principal Software Architect and technical leader with 11+ years building high-traffic, enterprise WordPress platforms and improving developer experience, performance, and reliability. Based in Portland, she leads a 17-person global team at Alley, combining hands-on PHP/JS engineering with product ownership to deliver secure, scalable publishing systems and measurable Core Web Vitals gains. She’s a WordPress core contributor who also contributes to high-profile ML and Windows ML projects on GitHub, bringing experience integrating DirectML/ONNX Runtime operators and UWP UI work to performance-sensitive systems. Linnea pairs rigorous backend performance tuning and deployment pipeline improvements with mentorship and cross-functional collaboration, and outside engineering she authors educational work on diabetes technology, reflecting a practical, user-centered approach to complex technical problems.
11 years of coding experience
10 years of employment as a software developer
Bachelor of Arts (B.A.), Neuroscience and Behavior, Bachelor of Arts (B.A.), Neuroscience and Behavior at Mount Holyoke College
English
Github Skills (16)
uwp10
machine-learning10
c-language10
onnx10
front-end-development10
csharp10
mvvm10
xaml10
cprogramming-language10
dotnet-core10
hardware-acceleration9
deeplearning-ai9
deep-learning9
windows9
tensorflow7
Programming languages (4)
Github contributions (5)
microsoft/Windows-Machine-Learning
May 2020 - Sep 2022
Samples and Tools for Windows ML.
Role in this project:
Front-end Developer
Front-end DeveloperContributions:61 reviews, 113 commits, 31 PRs in 2 years 4 months
Contributions summary:Linnea's commits primarily revolve around the development and improvement of UI components and their integration with the application's underlying architecture. The user focused on connecting buttons to the ViewModel and integrating commands from media selection controls, indicating a focus on user interaction and application workflow. Code changes in C# files suggest the user is building out UWP UI features within the context of the Windows Machine Learning repository, in a style transfer demonstration.
pytorchcaffe2pythonwindowswinmltools
microsoft/onnxruntime
May 2020 - Mar 2022
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Role in this project:ML Engineer
ML EngineerContributions:28 reviews, 2 commits, 38 PRs in 1 year 10 months
Contributions summary:Linnea contributed to the implementation and testing of various operators within the ONNX Runtime, a high-performance machine learning inferencing accelerator. Their work includes adding registrations for DML (DirectML) operators, specifically focusing on opset 18 and 19 features such as Reduce, Pad, Bitwise operations, and Resize. These contributions involved modifications to core provider files, test files, and operator registration to support new functionality and ensure compatibility across different execution providers.
runtimetrainingtensorflowai-frameworkaccelerator
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