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.