Remote GitHub Contributor: Code, Debug & Refactor Expert

YO AI Labs; Chicago (IL); Remote; USD 83,000 - 165,000; Part time

Job summary

YO AI Labs is seeking a GitHub Contributor for a remote, contract-based position. You will provide expert code samples, debugging guidance, and design insights across Python, Java, Rust, Go, C++, or TypeScript.

You will analyze defects, implement scalable features, refactor legacy code, and document decisions to support AI training data quality. Collaboration across teams and strong communication are essential.

Qualifications

• Hands-on expertise in at least one of Python3, Java, Rust, Go, C++, or TypeScript.
• Deep understanding of algorithms, data structures, and software engineering principles.
• Proven ability to debug complex systems and deliver optimizations.
• Experience with large codebase refactoring and legacy modernization.
• Track record of delivering high-impact features from conception to delivery.
• Strong documentation and communication skills to convey technical concepts.
• Interest in AI and its technical challenges.

Responsibilities

• Contribute expert-level code samples, debugging strategies, and development insights in Python3, Java, Rust, Go, C++, or TypeScript.
• Analyze, troubleshoot, and resolve complex software defects and performance bottlenecks in diverse codebases.
• Implement robust new features with scalability and maintainability in mind.
• Refactor and optimize legacy code to improve clarity and reliability.
• Document technical reasoning, solution approaches, and code decisions for AI training data quality.
• Review and validate peer-contributed code and submissions for accuracy and clarity.

Skills

Python3

Java

Rust

Go

C++

TypeScript

Algorithms

Data structures

Software engineering

Debugging

Documentation

Job description

YO AI Labs is seeking a GitHub Contributor for a remote, contract-based position. You will provide expert code samples, debugging guidance, and design insights across Python, Java, Rust, Go, C++, or TypeScript.

You will analyze defects, implement scalable features, refactor legacy code, and document decisions to support AI training data quality. Collaboration across teams and strong communication are essential.