We are sharing a specialised part-time consulting opportunity for experienced software engineers with strong expertise in Python, Java, Rust, C++, Go, TypeScript, algorithms, debugging, feature implementation, refactoring, and performance optimisation to contribute to an advanced AI training and software-engineering evaluation project.
Selected professionals will create reinforcement-learning environments that test an AI model's ability to solve complex software-engineering problems using Model Context Protocol (MCP) tools. The work combines realistic codebase tasks, tool-based reasoning, deterministic verification, and the creation of high-quality reference solutions. No prior experience in AI is required.
Key Responsibilities
Reinforcement Learning Environment Development
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Create reproducible environments for evaluating advanced software-engineering capability
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Design tasks requiring agents to interact with and reason over real MCP servers
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Build scenarios that test practical engineering ability rather than isolated code generation
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Ensure environments accurately measure both tool use and software-engineering performance
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Maintain consistency and reproducibility across evaluation runs
Software Engineering Task Design
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Create realistic tasks involving bug fixing, feature implementation, refactoring, and performance optimisation
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Develop scenarios based on existing codebases and practical engineering constraints
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Design tasks that require meaningful reasoning across algorithms, data structures, and system behaviour
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Define clear success criteria and expected outcomes
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Balance technical complexity with reliable evaluability
Golden Solutions & Verification
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Develop high-quality golden reference solutions
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Create deterministic verification logic for task completion
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Validate expected behaviours, edge cases, and failure conditions
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Ensure evaluation systems distinguish correct from partially correct implementations
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Maintain stable and reproducible grading criteria
Debugging, Refactoring & Performance
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Diagnose and resolve complex software issues
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Implement maintainable features in existing codebases
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Refactor code while preserving intended functionality
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Identify performance bottlenecks and scalability issues
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Apply strong engineering judgement to maintainability, efficiency, and code quality
Technical Review & Engineering Standards
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Review task quality, code correctness, and verification robustness
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Contribute to software-engineering best practices
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Participate in rigorous technical and code-review workflows
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Document assumptions, design decisions, and implementation details clearly
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Collaborate effectively with distributed technical teams
Ideal Profile
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Strong proficiency in one or more of C++, Python, Java, Go, TypeScript, or Rust
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Deep understanding of algorithms, data structures, and performance tuning
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Demonstrated experience debugging complex software issues
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Strong background in feature implementation and codebase refactoring
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Proven ability to optimise software for performance and scalability
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Experience working with large-scale or distributed codebases is highly valuable
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Familiarity with rigorous code-review processes and software-engineering standards
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Strong written and verbal communication skills
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High attention to technical detail and reproducibility
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Familiarity with modern AI or machine-learning systems is beneficial but not required
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Prior experience in AI training or model evaluation is not required
Engagement Details
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Part-time independent contractor engagement
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Fully remote
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Compensation: $60–$120/hour
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Expected commitment: approximately 15 hours per week
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Schedule is flexible, including evenings or weekends if preferred
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Compensation is output-based, with payment made for tasks that meet project specifications
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Minimum weekly submission requirements apply
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Work will involve reinforcement-learning environment design, MCP tool use, software-engineering task creation, deterministic verification, and golden reference solutions
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The selection process may include screening questions, an approximately 30-minute AI interview, a technical assessment, and hiring-manager review
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Selected professionals should be prepared to begin their first tasks within approximately 24–48 hours of completing onboarding
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Roles are typically filled within approximately 48 hours
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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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