David Bielejeski
Full Stack Engineer at Best Buy
Saint Paul, Minnesota, United States
Summary
🤩
Rockstar🎓
Top SchoolDavid Bielejeski is a Full Stack Engineer with 11 years of experience building resilient, user-focused web applications across Angular, .NET Core, TypeScript and modern front-end frameworks. He has led complex enterprise projects and microfrontend architectures for companies like CHS and Best Buy, improving performance and developer workflows while shipping client-side PDF/Excel reporting and robust GraphQL integrations. A pragmatic problem-solver, David routinely resurrects stalled projects—rewriting backends, enforcing DB constraints, and cutting report generation from tens of seconds to under two. He’s an active open-source maintainer (notably a popular mask-generator repo with 362 stars and frequent clones) and contributes to AI/vision ML tooling such as Dreambooth Stable Diffusion. Based in Saint Paul, MN, he blends hands-on engineering, cross-team collaboration with UI/UX, and a continuous curiosity for new languages and models like Bun, Python, and diffusion-based image models.
11 years of coding experience
14 years of employment as a software developer
University of Minnesota Twin Cities
Github Skills (10)
notebook10
pytorch10
machine-learning10
jupyter-notebook10
artificial-intelligence10
stable-diffusion10
image-generation10
python10
ai10
huggingface-transformers9
Programming languages (4)
Github contributions (5)
JoePenna/Dreambooth-Stable-Diffusion
Sep 2022 - Jan 2023
Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) by way of Textual Inversion (https://arxiv.org/abs/2208.01618) for Stable Diffusion (https://arxiv.org/abs/2112.10752). Tweaks focused on training faces, objects, and styles.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:11 reviews, 83 commits, 58 PRs in 3 months
Contributions summary:David appears to be actively working on the implementation and refinement of a Dreambooth implementation for Stable Diffusion. Their commits showcase modifications to the main application file, which includes changes to the training process. They are also involved in the creation of a Google Colab notebook, indicating a focus on making the Dreambooth training process accessible to users. Furthermore, the user is contributing to the repository by adding features like checkpoint saving and pruning, while maintaining the project's codebase.
dreamboothstable-diffusiontextualaitxt2img
djbielejeski/Stable-Diffusion-Regularization-Images-scarlett_johansson
Sep 2022 - Sep 2022
Contributions:1 commit, 1 branch in 1 day
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