We are sharing a specialised consulting opportunity for experienced Senior Software Engineers with strong expertise in software development, debugging, feature implementation, codebase refactoring, performance optimisation, algorithms, and production-quality engineering to contribute to an advanced AI training and reinforcement-learning environment project.
Selected professionals will create reproducible reinforcement-learning environments that test advanced AI systems on realistic software-engineering problems involving bug fixing, feature development, refactoring, and performance optimisation. The work requires strong technical judgement, robust reference solutions, and clear documentation of implementation decisions. No prior experience in AI is required.
Key Responsibilities
Software Engineering Environment Development
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Create realistic reinforcement-learning environments based on software-engineering problems
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Design tasks involving bug fixing, feature implementation, refactoring, and optimisation
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Build reproducible technical environments with clearly defined expected outcomes
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Develop golden reference solutions demonstrating correct implementations
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Ensure tasks reflect authentic engineering challenges across varied codebases
Debugging & Defect Resolution
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Analyse and troubleshoot complex software defects
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Identify root causes across unfamiliar or evolving codebases
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Develop reliable fixes while preserving existing system behaviour
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Apply structured debugging strategies to technically difficult problems
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Validate solutions for correctness, maintainability, and unintended regressions
Feature Development & Software Quality
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Implement robust features across existing software systems
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Apply sound algorithms, data structures, and software-engineering principles
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Design solutions with scalability and long-term maintainability in mind
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Follow established engineering practices and code-quality standards
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Contribute expert-level implementation approaches across supported languages
Refactoring & Performance Optimisation
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Refactor legacy or complex code to improve clarity and maintainability
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Identify performance bottlenecks and inefficient implementation patterns
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Optimise code for execution efficiency and system reliability
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Support modernisation of existing software architectures where appropriate
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Balance performance improvements with readability and technical quality
Validation, Review & Documentation
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Document technical reasoning, implementation choices, and solution approaches
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Review and validate technical submissions for correctness and clarity
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Evaluate peer-contributed code against project requirements
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Provide structured feedback on weak or incomplete engineering solutions
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Maintain clear technical documentation supporting reproducibility and AI evaluation
Ideal Profile
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Significant hands-on expertise in at least one of Python 3, Java, Rust, Go, C++, or TypeScript
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Strong understanding of algorithms, data structures, and core software-engineering principles
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Proven ability to debug complex systems and resolve difficult software defects
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Strong feature-development experience across production codebases
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Experience refactoring large or legacy codebases
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Demonstrated performance-optimisation experience
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Ability to understand and work effectively within unfamiliar codebases
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Track record of delivering high-impact features from conception through implementation
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Strong judgement around code quality, maintainability, and reliability
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Ability to design reproducible technical environments and reference solutions
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Strong technical documentation and written communication skills
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Experience reviewing or validating other engineers' code is advantageous
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Curiosity about AI systems and technical evaluation is beneficial
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No prior AI-training or model-evaluation experience is required
Engagement Details
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Independent contractor engagement
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Fully remote
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Expected commitment: approximately 15 hours per week
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Displayed compensation range: $100–$150/hour
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Actual compensation structure is output-based, with payment made per task that meets project specifications
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Task completion time may vary depending on individual experience and workflow
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Minimum weekly submission requirements apply; the source does not specify the exact number of required tasks
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Work will involve reinforcement-learning environments, debugging, feature implementation, refactoring, performance optimisation, validation, and golden reference solutions
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Roles are typically filled within approximately 48 hours
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Selected experts are expected to begin initial tasks within approximately 24–48 hours after onboarding
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Project scope, workload, codebases, programming languages, and evaluation standards may evolve depending on project requirements
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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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