ML Task Auditor - Applied ML

About The Job 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 Compensation: $70–$90/hour Location: Remote Role 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.

Application Process (Takes 20–30 mins to complete)

• Upload resume
• AI interview based on your resume
• Submit form

Resources & Support

• For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
• For any help or support, reach out to: [email protected]

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.