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Open nowFirst seen 5 hours ago

Remote | Software Engineer (GitHub Contributor) — $50–$100/hour

24-MAG324 open roles

Where
New York, United States, Remote
Work mode
Remote
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Your applicationOpen nowRemote | Software Engineer (GitHub Contributor) — $50–$100/hour24-MAG · New York, United States, Remote

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market. 24-MAG postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.5%14 days
  5. 35.5%30 days
  6. 45.1%60 days
This job: first seen 5 hours ago

24-MAG median: 1 days open

The posting

We are sharing a specialised remote consulting opportunity for experienced Software Engineers and GitHub Contributors with strong expertise in backend development, open-source software, algorithms, codebase refactoring, debugging, and performance optimisation to contribute their technical knowledge to advanced AI training and evaluation initiatives.

Selected professionals will develop realistic software engineering challenges, construct reproducible reinforcement learning environments, implement deterministic verification systems, and produce accurate reference solutions for complex programming tasks. The work combines practical engineering expertise with codebase analysis, feature implementation, automated testing, and technical evaluation to improve the coding, debugging, and problem-solving capabilities of advanced AI systems. Prior experience with AI training projects is not required.

Key Responsibilities

Software Engineering & Coding Challenge Development

  • Design realistic, technically challenging programming tasks based on practical software engineering scenarios
  • Develop self-contained coding problems involving bug fixes, feature implementation, refactoring, and performance optimisation
  • Apply expertise in Python 3, Java, Rust, Go, C++, TypeScript, or comparable programming languages
  • Analyse unfamiliar codebases and translate technical requirements into clear, implementable engineering objectives
  • Create coding challenges that reflect authentic software development workflows, system constraints, and engineering best practices

Reinforcement Learning Environments & Deterministic Verification

  • Build reproducible reinforcement learning environments for evaluating advanced AI coding capabilities
  • Design deterministic verification systems that correctly recognise valid software implementations
  • Develop comprehensive automated tests that identify incorrect solutions while accepting reasonable alternative implementations
  • Produce accurate golden reference solutions for assigned programming challenges
  • Validate evaluation environments for reproducibility, technical correctness, and consistency with specified requirements

Backend Development & Feature Engineering

  • Develop and evaluate backend services, APIs, and supporting application components
  • Implement robust software features while maintaining scalability, reliability, and code quality
  • Apply appropriate algorithms, data structures, and software design principles to complex engineering problems
  • Assess code architecture, system behaviour, and implementation decisions against technical requirements
  • Contribute practical development expertise to realistic feature delivery and software engineering scenarios

Debugging, Refactoring & Performance Optimisation

  • Investigate complex software defects, implementation errors, and performance bottlenecks across diverse codebases
  • Apply systematic debugging approaches to identify underlying issues and implement effective corrections
  • Refactor existing and legacy code to improve readability, maintainability, efficiency, and long-term reliability
  • Evaluate computational performance, runtime behaviour, and software resource utilisation
  • Verify engineering improvements through automated testing, reproducible execution, and structured technical analysis

Code Review, Technical Documentation & Quality Assurance

  • Review programming solutions and technical submissions for correctness, clarity, efficiency, and maintainability
  • Evaluate peer-contributed code and provide precise, actionable engineering feedback
  • Document technical reasoning, implementation decisions, debugging strategies, and verification methodologies
  • Communicate sophisticated software engineering concepts through clear written explanations and structured evaluations
  • Maintain high standards of technical accuracy, reproducibility, and documentation quality across assigned deliverables

Ideal Profile

  • Significant hands-on experience in professional software engineering, particularly backend development and complex application systems
  • Demonstrated expertise in at least one of the following programming languages: Python 3, Java, Rust, Go, C++, or TypeScript
  • Strong understanding of algorithms, data structures, computational complexity, and foundational computer science principles
  • Proven experience developing scalable backend services, APIs, and production software applications
  • Practical expertise in debugging, automated testing, code review, and technical problem-solving
  • Demonstrated ability to identify and resolve complex software defects and system performance bottlenecks
  • Experience implementing substantial features within existing applications or large-scale codebases
  • Strong understanding of software architecture, refactoring, maintainability, and legacy system modernisation
  • Experience designing reproducible tests and validating implementations against technical specifications
  • Ability to develop objective acceptance criteria and explain why a programming solution satisfies defined requirements
  • Demonstrable GitHub or comparable open-source contributions are preferred; candidates without a sufficiently representative portfolio may complete an alternative HackerRank assessment
  • Experience contributing to open-source repositories, reviewing pull requests, or maintaining collaborative software projects is highly relevant
  • Strong analytical reasoning, logical thinking, algorithmic problem-solving, and independent engineering judgement
  • Ability to navigate unfamiliar codebases and understand complex technical requirements efficiently
  • Excellent technical documentation skills, including the ability to explain programming decisions and software modifications clearly
  • Strong written communication and constructive code review capabilities
  • Experience working independently on technical assignments and producing reproducible software deliverables
  • Familiarity with reinforcement learning environments, coding benchmarks, or AI software engineering evaluation is advantageous
  • Interest in advanced AI technologies and automated programming systems is beneficial
  • Prior experience with AI model training or evaluation projects is not required

Engagement Details

  • Freelance / contract engagement
  • Fully remote — open worldwide
  • Compensation: $50–$100/hour advertised rate range
  • Payment Structure: Output-based compensation, with payment made per completed task that meets project specifications
  • Estimated Task Duration: Approximately 15 hours per task/run
  • Minimum weekly task submission requirements apply
  • 100 available openings
  • Specialised software engineering consulting role spanning GitHub contributions, backend development, reinforcement learning environments, and AI coding evaluation
  • Technical Focus: Python 3, Java, Rust, Go, C++, TypeScript, debugging, feature implementation, refactoring, and performance optimisation
  • Portfolio Requirement: Demonstrable open-source contributions through GitHub or a comparable profile; an alternative technical assessment may be required
  • Work will involve developing coding challenges, building reproducible evaluation environments, implementing deterministic verifiers, and producing golden reference solutions
  • Assignments will require accurate programming implementations, automated validation, and clear documentation of technical decisions
  • Selection may include screening questions, an approximately 20-minute AI interview, a technical assessment where applicable, and a hiring manager review
  • Assessment Requirement: Interviews and technical assessments must be completed independently, without AI assistants or help from other individuals
  • Selected professionals should be prepared to begin initial assignments within 24–48 hours of completing onboarding
  • Previous experience with AI training projects is not required
  • 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

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