Anyone AI · Software & coding
Senior Software Engineer - Open Source & SWE-Bench Evaluation
Listed on Anyone AI as “Senior Software Engineer - Open Source & SWE-Bench Evaluation”
How this rate compares
This listing
$65 per hour
Typical in Software & coding
$45–$80 per hour
Within the typical range
Typical: the middle of the lowest and highest rates posted by 145 listings in this category on MantaWork, in US dollars.
What this actually is
You review AI-generated code, rank model outputs against each other, write prompts that test edge cases, and provide expert feedback that gets used to train coding models. Not shipping production software. The platform title (Senior Software Engineer - Open Source & SWE-Bench Evaluation) reflects the rate band and the expertise required, not the day-to-day work.
Original posting from Anyone AI
Work location: Remote (Argentina)
Pay: $65 per hour, as the posting states it.
Anyone AI is recruiting experienced Software Engineers for a specialized project focused on reviewing and evaluating real-world software engineering tasks derived from open-source repositories.
The work involves assessing whether coding tasks based on real GitHub issues and pull requests are technically sound, reproducible, appropriately tested, and representative of the kinds of problems professional software engineers solve every day.
WHAT YOU’LL WORK ON
You’ll review software engineering tasks involving:
- Real-world bug fixes and feature implementations
- Open-source repositories and pull requests
- Unit tests and test coverage
- Repository setup and dependency management
- Reproducibility and environment configuration
- Task difficulty and complexity
- Multi-file and cross-module code changes
- Technical feedback and quality assessment
You’ll determine whether tasks are clearly specified, technically solvable, supported by sufficient tests, and free from issues such as flaky tests, missing dependencies, ambiguous requirements, or environment-specific behavior.
WHAT WE’RE LOOKING FOR
- 3+ years of professional software engineering experience
- Strong experience working with large, multi-file codebases
- Experience reviewing pull requests, debugging issues, and maintaining production code
- Strong understanding of unit testing and test coverage
- Ability to evaluate whether tests correctly validate a solution without unnecessarily restricting implementation approaches
- Experience with dependency management, environment setup, and reproducibility
- Strong understanding of Git and GitHub-based development workflows
- Ability to analyze complex technical problems and provide clear written feedback
NICE TO HAVE
- Contributions to or maintenance of open-source projects
- Experience with SWE-Bench, SWE-Bench Verified, or similar coding benchmarks
- Experience with major Python open-source projects such as Django, Flask, scikit-learn, SymPy, matplotlib, requests, or pytest
- Experience with Docker, CI/CD, pip, conda, or dependency pinning
- Knowledge of test fixtures, test isolation, or property-based testing
- Experience designing technical assessments or reviewing coding challenges
- Experience with AI/ML evaluation, data curation, RLHF, or benchmark development
WHAT YOU’LL BE RESPONSIBLE FOR
- Reviewing coding tasks derived from real GitHub issues and pull requests
- Assessing whether problem statements and success criteria are clear and complete
- Evaluating unit tests for correctness, coverage, and robustness
- Identifying flaky tests, missing dependencies, version conflicts, and environment issues
- Determining whether tasks can be reliably reproduced across environments
- Assessing the real-world difficulty and complexity of each task
- Providing clear recommendations on whether tasks should be accepted, improved, or excluded
ENGAGEMENT
Work Type: Remote
Engagement: Part-time, project-based consulting
Focus: Software engineering, open-source code review, testing, and technical evaluation
This role is a strong fit for experienced engineers who enjoy debugging complex codebases, reviewing pull requests, working with open-source software, and evaluating what makes a software engineering problem well designed.
Quoted from Anyone AI's public listing on 2026-11-15. We don't edit platform copy; honest framing is in the title and the “what this actually is” block above.
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