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ML Challenge Task Auditor

up to $90/hr

source wording: “70–90 USD HOUR”

What this role asks for

  • PyTorch
  • TensorFlow
Read from the posting's own words: show the exact sentences
  • PyTorch: “…and train/test/CV hygiene • Proficiency with standard ML frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost) • Ability to critique ML claims against evidence and…”
  • TensorFlow: “…hygiene • Proficiency with standard ML frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost) • Ability to critique ML claims against evidence and reproduce…”

The role, as Mercor describes it

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)

Read the rest of the description (3 more paragraphs)

• 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.

Posted by Mercor, reproduced here so you can judge the role before clicking. Original posting ↗

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Source: platform job feed · first seen 9d ago · ID list_AAABoEpzlEigUmznqXNFkJZb

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up to $90/hrMercor · ML Challenge Task Auditor

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