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About the Role
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.
What You'll Do
You're a Good Fit If You
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
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.
Independent contractor engagement. Apply via the link below - Mercor handles onboarding and pays weekly via Stripe or Wise.
Common Questions
Mercor has a reliability rating of very reliable based on the listings we track, with an onboarding time of 1-3 weeks (interview + assessment + trial). See our full Mercor review for the details behind that rating.
Applying takes you to Mercor's own website, where the application is completed. We are not a recruiter or employer and do not process applications directly - we may be recorded as the referring source.
$70-$90/h - Independent contractor engagement. Apply via the link below - Mercor handles onboarding and pays weekly via Stripe or Wise.
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.
