Daniel Treiman
Director Of Software Engineering at Xcimer Energy
Denver Metropolitan Area United States
Summary
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Rockstar🎓
Top SchoolDaniel Treiman is a Principal Computational Engineer with 11+ years building production-grade modeling, simulation, and ML systems across startups and large tech firms. He blends a strong computer science and math foundation with hands-on experience in rapid prototyping, custom compilers/code generation, HPC, and deployment infrastructure, having held technical leadership roles at Predibase, AliveCor, and Google and co-founded GameSalad. Daniel moves fluidly between R&D and product engineering—shipping ML-enabled medical devices, contributing QA and test automation to the low-code Ludwig AI project, and architecting scalable systems for energy and consumer platforms. He advises early-stage startups and brings uncommon depth in tooling and compiler-style automation that accelerates model development and deployment.
11 years of coding experience
22 years of employment as a software developer
B.S. with Honors Computer Science, B.S. with Honors Computer Science at Gustavus Adolphus College
Stackoverflow
51reputation
14kreached
1answer
0questions
Github Skills (12)
unit-testing10
machine-learning10
pytorch10
pytest10
python9
test-automation9
neural-network9
deep-learning8
data-science8
xcode6
uicollectionview6
pagination6
Programming languages (6)
Github contributions (5)
ludwig-ai/ludwig
Dec 2021 - Jan 2023
Low-code framework for building custom LLMs, neural networks, and other AI models
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:182 reviews, 84 commits, 155 PRs in 1 year 1 month
Contributions summary:Daniel's commits primarily focus on adding and modifying unit tests for the `ludwig-ai/ludwig` repository. They have written tests for categorical encoders, generic encoders, and reduction modules, demonstrating an understanding of the library's architecture. Additionally, the user has addressed code review comments and added type annotations to improve the quality and maintainability of the test code. These contributions indicate a focus on ensuring the reliability and correctness of the library's functionality.
ailow-codeneural-networkdeep-learningmachine-learning
dantreiman/neural-style-tf
Sep 2018 - Apr 2020
TensorFlow (Python API) implementation of Neural Style
Contributions:207 commits, 194 pushes, 37 branches in 1 year 7 months
pythontensorflow
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