Data annotation job
SWE-Bench Task Auditor
Mercor · Posted 2 months ago
- AI evaluation
- Coding
About this role
Evaluate the quality, correctness, and reproducibility of software-engineering benchmark tasks used to train and evaluate a frontier AI lab's models. You'll assess repository-level tasks, reference patches, test harnesses, and grading integrity, and provide clear, rubric-based written feedback.
Basic Qualifications
- 3+ years professional software engineering
- Real open-source contribution or maintainer experience (merged PRs, committer / maintainer roles)
- Strong ability to audit reference patches, test runners, and Docker isolation, and to detect answer leakage / reward hacking
- Fluency across common ecosystems (Python and at least one of Java / Go / TypeScript / C++)
Preferred Qualifications
- Familiarity with SWE-Bench (Verified) or similar repository benchmarks
- Maintainer history on major Python OSS (Django, Flask, scikit-learn, sympy, pytest, etc.)
- Prior code-review or task-grading experience
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Mercor is an AI-native talent marketplace connecting vetted domain experts such as doctors, lawyers, and engineers directly with frontier AI labs for RLHF, evaluation, and specialized training data at massive scale. See all Mercor jobs.
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