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ML Challenge Task Auditor

Mercor
Data analysis
Remote
Contract

$70 to $90/hIndicative range provided by Mercor

Posted on August 28, 2026 · Applications until October 18, 2026

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This remote role involves evaluating the quality, correctness, and methodological rigor of applied machine learning tasks to provide clear written feedback. Candidates need at least three years of hands-on applied machine learning experience and proficiency with standard frameworks like PyTorch and TensorFlow.

Description in English, as published by Mercor.

Evaluate the quality, correctness, and methodological rigor of applied machine-learning tasks used to train and evaluate a frontier AI lab's models. You'll assess experiment design, model-selection reasoning, and evaluation methodology, and provide clear, rubric-based written feedback.

Basic Qualifications • 3+ years hands-on applied/experimental ML (experiment design, model selection, hyperparameter tuning, evaluation methodology) • Strong grasp of data-quality rigor: leakage detection, metric gaming, and train/test/CV hygiene • Proficiency with standard ML frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost) • Ability to critique ML claims against evidence and reproduce results

Preferred Qualifications • Competition / benchmark experience (e.g., Kaggle) • Graduate research or publication record in applied ML • Prior task-grading or peer-review experience

Note: this role evaluates applied/experimental ML rigor, it is not an LLM-application-building or MLOps role.

3 openings

About Mercor

Mercor is a US marketplace hiring remote experts for AI and consulting projects, from law to engineering. The original posting is on their site.

View this job on Mercor

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