Remote | GitHub Contributor — $50–$100/hour

24-Mag•New York, NY

1d•Remote

About The Position

We are sharing a specialised part-time consulting opportunity for experienced software engineers with strong open-source contributions and demonstrable GitHub or GitLab profiles to contribute to an advanced AI training and software engineering evaluation project. Selected professionals will create reproducible reinforcement-learning environments designed to test advanced AI systems on realistic software engineering problems involving bug fixing, feature implementation, codebase refactoring, and performance optimisation. The work requires strong hands-on engineering expertise, high-quality public code contributions, and the ability to develop rigorous reference solutions and clearly document technical reasoning. No prior experience in AI is required.

Requirements

Clear and demonstrable open-source contributions through GitHub, GitLab, or comparable public development profiles
Significant hands-on expertise in at least one of Python3, Java, Rust, Go, C++, or TypeScript
Deep understanding of algorithms, data structures, and software engineering fundamentals
Proven ability to debug complex systems and resolve technically challenging software defects
Strong experience implementing robust software features
Experience with performance optimisation and technical bottleneck analysis
Strong ability to reason about code correctness, maintainability, and system behaviour
Excellent technical documentation and communication skills
Ability to review other engineers' code and identify technical weaknesses precisely
Applicants must be able to demonstrate meaningful open-source contributions through a public GitHub, GitLab, or comparable profile

Nice To Haves

Background in large-codebase refactoring or legacy-system modernisation is advantageous
Track record of delivering meaningful technical contributions from conception through implementation
Interest in AI systems and technical evaluation is beneficial
No prior experience in AI training is required

Responsibilities

Contribute expert-level code samples and development solutions in Python3, Java, Rust, Go, C++, TypeScript, or comparable languages
Apply experience gained from real-world open-source or production codebases
Implement robust functionality while considering scalability, maintainability, and software quality
Demonstrate sound software engineering judgement across complex development tasks
Produce solutions that can be independently reproduced and validated
Analyse, troubleshoot, and resolve complex software defects across diverse codebases
Identify root causes of incorrect behaviour, regressions, and system failures
Implement new features from requirements through validated delivery
Diagnose and resolve performance bottlenecks and inefficient implementation patterns
Address edge cases and ensure solutions remain reliable across relevant scenarios
Refactor legacy or complex code to improve clarity, maintainability, and long-term reliability
Identify architectural or implementation weaknesses within existing systems
Improve software performance while preserving functional correctness
Evaluate trade-offs between development speed, scalability, complexity, and maintainability
Modernise codebases where appropriate without introducing unnecessary regressions
Create reinforcement-learning environments that evaluate AI systems on realistic software engineering tasks
Develop reproducible problem environments and corresponding golden reference solutions
Design tasks involving bug fixing, feature implementation, codebase refactoring, and optimisation
Document technical reasoning, implementation decisions, and verification methodology clearly
Review and validate peer-contributed code and technical submissions for correctness and clarity