Remote | GitHub Contributor - $50-$100/hour

About the job Remote | GitHub Contributor - $50-$100/hour

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.

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