GitHub Contributor

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. Key Responsibilities - Software Engineering & Open-Source Contribution - 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 - Debugging & Feature Development - 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 - Refactoring & Performance Optimisation - 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 - AI Evaluation Environments & Reference Solutions - 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 Ideal Profile - 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 - Background in large-codebase refactoring or legacy-system modernisation is advantageous - Track record of delivering meaningful technical contributions from conception through implementation - 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 - Interest in AI systems and technical evaluation is beneficial - No prior experience in AI training is required Engagement Details - Part-time independent contractor engagement - Fully remote - Compensation: $50–$100/hour - Expected commitment: approximately 15 hours per week - Compensation is output-based, with payment made for tasks that meet project specifications - Minimum weekly submission requirements apply - Applicants must be able to demonstrate meaningful open-source contributions through a public GitHub, GitLab, or comparable profile - Work will involve software engineering, reinforcement-learning environment creation, debugging, feature development, refactoring, optimisation, and reference-solution development - The selection process may include screening questions, an approximately 30-minute AI interview, a technical assessment, and hiring-manager review - Selected professionals should be prepared to begin their first tasks within approximately 24–48 hours of completing onboarding - Roles are typically filled within approximately 48 hours - Project scope, workload, task complexity, and evaluation standards may evolve depending on project requirements - Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party About the Platform - This opportunity is available through 24-MAG LLC - We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams - By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy