Wesley Eldridge
Owner at Rebellious Labs
Tuscaloosa, Alabama, United States
Summary
👤
Senior🎓
Top SchoolWesley Eldridge is a product-focused software engineer and entrepreneur with 12 years of experience building mobile and web applications, APIs, and developer-led businesses from Tuscaloosa, Alabama. As owner of Rebellious Labs and former engineering manager at Copysmith, he blends hands-on full-stack development with project leadership and client consulting to deliver intuitive, scalable experiences. His work spans front-end React and Backbone, .NET back-ends, and integrations with systems like Salesforce and WordPress, plus team and SSO solutions. An avid builder beyond software—hardware, robots, and startups—he’s contributed meaningful UI and backend improvements to multi-agent learning research tooling, migrating serialization to JSON and enhancing game rendering. Driven by an entrepreneurial spirit and a focus on simplicity, he consistently turns complex requirements into elegant, user-centered products.
12 years of coding experience
15 years of employment as a software developer
BS Applied Economics, BS Applied Economics at The University of Alabama
Stackoverflow
71reputation
2kreached
8answers
0questions
Github Skills (24)
json10
python10
rendering10
graphic10
render10
pyglet10
game-development10
file-access9
fileio9
file-handling9
file-processing9
docker8
dockers8
cicd7
lightbox6
Programming languages (8)
Github contributions (5)
MultiAgentLearning/playground
Feb 2018 - Apr 2019
PlayGround: AI Research into Multi-Agent Learning.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:28 commits, 30 PRs, 9 pushes in 1 year 1 month
Contributions summary:Wesley made significant contributions to the project, primarily focused on improving the user interface and game rendering, and also back-end changes. Key changes include modifying file formats from pickle to JSON for data serialization, which impacts data handling and storage. Additionally, they updated the graphics rendering system, including the introduction of new visual elements and support for team-based agent displays, enhancing the game's visual experience. Further, the user implemented features to support game state recording and retrieval in JSON format.
pytorchagentdeep-learningreinforcement-learningmachine-learning
weseldridge/playground
Feb 2018 - Oct 2018
PlayGround: AI Research into Multi-Agent Learning.
Contributions:90 pushes, 24 branches in 8 months
pytorchagentdeep-learningreinforcement-learningmachine-learning
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