An older role: first posted 39d ago, and AI expert network still listed it when we checked today. Newer roles tend to fill faster. See the jobs hiring now.
What the work is
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
Pay
$70–90/hr, fully remote.