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Open nowFirst seen 5 hours ago

Remote | Software Engineer (Open Source 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 (Open Source 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 Open Source Contributors with strong expertise in backend development, algorithms, software debugging, codebase refactoring, automated testing, and performance optimisation to contribute their technical knowledge to advanced AI training and evaluation initiatives.

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

Key Responsibilities

Software Engineering & Coding Challenge Development

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

Reinforcement Learning Environments & Automated Verification

  • Build reproducible reinforcement learning environments designed to evaluate advanced AI coding capabilities
  • Develop deterministic verification systems that distinguish valid solutions from incorrect implementations
  • Create accurate golden reference solutions for assigned software engineering challenges
  • Implement automated tests and objective acceptance criteria to assess solution correctness
  • Ensure evaluation environments are reproducible, technically rigorous, and suitable for assessing different valid implementation approaches

Backend Development & Feature Implementation

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

Debugging, Refactoring & Performance Optimisation

  • Analyse unfamiliar codebases to identify software defects, technical inconsistencies, and performance bottlenecks
  • Develop effective debugging strategies and implement appropriate software corrections
  • Refactor existing or legacy code to improve readability, maintainability, and long-term reliability
  • Evaluate computational efficiency, runtime behaviour, and relevant software performance characteristics
  • Validate engineering improvements through automated testing, reproducible execution, and technical analysis

Code Review, Documentation & Quality Assurance

  • Review submitted code and technical solutions for correctness, clarity, efficiency, and adherence to engineering standards
  • Evaluate peer-contributed implementations and provide structured, actionable technical feedback
  • Document programming decisions, debugging approaches, verification methods, and reference solutions
  • Communicate complex software engineering concepts clearly through technical explanations and written evaluations
  • Maintain high standards of reproducibility, implementation quality, and technical documentation across assigned deliverables

Ideal Profile

  • Significant hands-on software engineering experience, particularly in backend development and complex application systems
  • Demonstrated expertise in at least one of the following: Python 3, Java, Rust, Go, C++, or TypeScript
  • Strong understanding of algorithms, data structures, and foundational computer science principles
  • Proven experience developing scalable backend services, APIs, or production software applications
  • Practical expertise in software debugging, automated testing, code review, and technical problem-solving
  • Experience identifying and resolving complex software defects and performance bottlenecks
  • Demonstrated ability to implement substantial features within existing applications or large codebases
  • Strong understanding of codebase refactoring, software maintainability, and legacy system improvement
  • Experience developing reproducible tests and validating software implementations against technical requirements
  • Ability to design objective verification criteria and explain why a software solution satisfies specified constraints
  • Demonstrable open-source contributions through GitHub or a comparable public development profile are preferred; candidates without a sufficiently representative profile may complete a technical assessment
  • Experience collaborating on open-source software projects or reviewing external code contributions is highly relevant
  • Strong analytical reasoning, logical thinking, computational problem-solving, and independent engineering judgement
  • Ability to navigate unfamiliar codebases and understand complex software requirements efficiently
  • Excellent technical documentation skills, including the ability to explain algorithms, code changes, and implementation decisions 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, AI coding benchmarks, or software engineering evaluation systems is advantageous
  • Interest in advanced AI technologies and automated software engineering is beneficial
  • Prior experience with AI training or model 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 backend development, open-source software, 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 used
  • Work will involve developing realistic coding challenges, building reproducible evaluation environments, implementing deterministic verifiers, and producing golden reference solutions
  • Assignments will require technically accurate implementations, automated validation, and clear documentation of engineering decisions
  • Selection may include screening questions, an approximately 20-minute AI interview, a technical assessment where applicable, and a hiring manager review
  • Assessment Requirement: Interview and assessment stages 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
  • Prior 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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