Remote | AI Engineer — $60–$120/hour

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

• Create reproducible environments for evaluating advanced software-engineering capability
• Design tasks requiring agents to interact with and reason over real MCP servers
• Build scenarios that test practical engineering ability rather than isolated code generation
• Ensure environments accurately measure both tool use and software-engineering performance
• Maintain consistency and reproducibility across evaluation runs

Software Engineering Task Design

• Create realistic tasks involving bug fixing, feature implementation, refactoring, and performance optimisation
• Develop scenarios based on existing codebases and practical engineering constraints
• Design tasks that require meaningful reasoning across algorithms, data structures, and system behaviour
• Define clear success criteria and expected outcomes
• Balance technical complexity with reliable evaluability

Golden Solutions & Verification

• Develop high-quality golden reference solutions
• Create deterministic verification logic for task completion
• Validate expected behaviours, edge cases, and failure conditions
• Ensure evaluation systems distinguish correct from partially correct implementations
• Maintain stable and reproducible grading criteria

Debugging, Refactoring & Performance

• Diagnose and resolve complex software issues
• Implement maintainable features in existing codebases
• Refactor code while preserving intended functionality
• Identify performance bottlenecks and scalability issues
• Apply strong engineering judgement to maintainability, efficiency, and code quality

Technical Review & Engineering Standards

• Review task quality, code correctness, and verification robustness
• Contribute to software-engineering best practices
• Participate in rigorous technical and code-review workflows
• Document assumptions, design decisions, and implementation details clearly
• Collaborate effectively with distributed technical teams

Ideal Profile

• Strong proficiency in one or more of C++, Python, Java, Go, TypeScript, or Rust
• Deep understanding of algorithms, data structures, and performance tuning
• Demonstrated experience debugging complex software issues
• Strong background in feature implementation and codebase refactoring
• Proven ability to optimise software for performance and scalability
• Experience working with large-scale or distributed codebases is highly valuable
• Familiarity with rigorous code-review processes and software-engineering standards
• Strong written and verbal communication skills
• High attention to technical detail and reproducibility
• Familiarity with modern AI or machine-learning systems is beneficial but not required
• Prior experience in AI training or model evaluation is not required

Engagement Details

• Part-time independent contractor engagement
• Fully remote
• Compensation: $60–$120/hour
• Expected commitment: approximately 15 hours per week
• Schedule is flexible, including evenings or weekends if preferred
• Compensation is output-based, with payment made for tasks that meet project specifications
• Minimum weekly submission requirements apply
• Work will involve reinforcement-learning environment design, MCP tool use, software-engineering task creation, deterministic verification, and golden reference solutions
• 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
• 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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