AI training & evaluation
SWE-Bench Task Auditor
Mercor
Evaluate the quality, correctness, and reproducibility of software-engineering benchmark tasks used to train and evaluate a frontier AI lab's models.
- Work arrangement & location
- Remote · Current location: United States
- Engagement
- hourly
Location and residence requirements
- Current location
- United States
Employer’s location wording: Remote — United States
- Software Engineering
Employer description and requirements
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