David Welsch
Support Engineer at Identity Automation
Boise, Idaho, United States
Summary
🤩
Rockstar🎓
Top SchoolDavid Welsch is a Support Engineer based in Boise, Idaho with three years of focused experience in desktop and enterprise systems deployment, image creation, and endpoint management using Microsoft System Center and SCCM. He brings hands-on expertise across Windows imaging, Citrix XenApp, Apple iOS enterprise deployment, and RSA security tools, with a background supporting healthcare and identity-management environments. Known for practical problem solving and deskside troubleshooting, he has also contributed to open-source documentation for a Python orchestration project, improving onboarding and usability through clearer guides and visuals. That blend of frontline support, deployment automation, and documentation work makes him effective at translating complex infrastructure workflows into reliable, user-friendly processes.
3 years of coding experience
Computer Science, Computer Science at Bethany CollegeComputer networking and repair, Computer networking and repair at Westmoreland County Community College
Github Skills (6)
rs10
restructuredtext10
sphinx10
documentation10
markdown-it8
markdown8
Programming languages (4)
Github contributions (5)
AgnostiqHQ/covalent
Oct 2022 - Jan 2023
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
Role in this project:
Technical Writer
Technical WriterContributions:8 reviews, 24 commits, 12 PRs in 2 months
Contributions summary:David primarily focused on improving the project's documentation. Their commits involved extensive revisions and reorganization of the documentation, including the "Getting Started," "Quick Start," and UI reference sections. The user also added images, diagrams, and corrected broken links to enhance the clarity and usability of the documentation. These efforts improved the overall accessibility of the project.
high-performancepythonworkflow-automationwatsonscience
dwelsch-esi/aimet
Sep 2024 - Mar 2025
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
Contributions:3 PRs, 87 pushes, 80 branches in 6 months
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