- Listed at $70 to $90 an hour
- 40 hours a week
- Remote
Open to: United States
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You will review machine-learning tasks used to train and test AI models, checking whether the experiment design, model choices, and evaluation methods are sound. The role suits people with at least three years of hands-on applied ML, a sharp eye for data leakage and train/test hygiene, and fluency in tools like PyTorch or scikit-learn. It is remote for candidates in the United States and runs 40 hours a week. Pay is listed at $70 to $90/hr as of 2026-10-14.
This is a 100% remote role. Applicants must live in the United States.
- Field: Coding
- Posted 2026-08-28
Pay as listed on 2026-11-03.
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Questions About This Role
What Background Fits the ML Challenge Task Auditor Role?
The listing looks for experience with competitions or benchmarks such as Kaggle, a graduate research or publication record in applied machine learning, and some history grading tasks or reviewing others' work. Those three areas are the main qualifications named.
Is the ML Challenge Task Auditor Role Meant for MLOps or LLM App Building?
No. The listing says this job focuses on judging the rigor of applied and experimental machine learning work. It is not aimed at people who build LLM applications or handle MLOps, so those skills alone would not match.
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