Critically review machine learning papers for methodological soundness, novelty, and clarity.
Inspect Python source code and experimental logs to validate reported metrics against underlying data.
Conduct literature reviews using tools such as Google Scholar or Semantic Scholar to identify prior work, detect plagiarism, and assess research originality.
Provide structured feedback on “human-quality” research assessments and potential ethical or safety-related concerns.
Submit non-identifying background details (e.g., affiliation, highest degree, publication links) to establish evaluator credibility for the study.
Ideal Qualifications
Strong academic or professional background in artificial intelligence, machine learning, or related research domains.
Experience interpreting and analyzing ML papers; familiarity with top-tier venues (e.g., NeurIPS, ICLR, ICML) is preferred but not required.
Ability to read and evaluate Python code, experimental pipelines, and quantitative logs.
Demonstrated experience with academic literature review tools.
Doctoral students, industry researchers, and published authors are encouraged to provide services.
High attention to detail and ability to assess complex technical arguments.
Contract Terms
Payments are issued regularly based on completed work via Mercor’s platform.
Start date: Immediate.
Application Process
Submit your resume or CV to begin.
Complete a brief form outlining your technical background and relevant publications.
Additional screening questions or sample evaluations may be requested to confirm expertise.
You will be contacted with next steps shortly after submission.
