Machine Learning Evaluator - AI Trainer

About the role

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: ML Challenge Task Auditor Type: Contract Location: Remote.

Responsibilities

• Evaluate the quality, correctness, and methodological rigor of applied machine-learning tasks for training and evaluating models.
• Assess experiment design, model-selection reasoning, and evaluation methodology.
• Provide clear, rubric-based written feedback to improve AI model performance.
• Review and critique ML claims against evidence and reproduce results.
• Work independently and asynchronously to meet deadlines while enhancing model outputs.

Qualifications

Must-Have:

• 3+ years hands-on applied/experimental ML experience.
• 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:

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

Pay

$70–$90/hour