$35-70/hrAs published by the platform.
This role involves reviewing and validating econometric questions, models, and explanations used in AI training datasets. Instructors with expertise in econometrics and quantitative economics will assess statistical accuracy, identify errors in AI-generated economic reasoning, and provide structured feedback to improve model outputs. The work is remote and asynchronous, suited for experienced econometrics educators.
$35-70/hr
Pay as published by the platform. It is not a guarantee of income or hours.
The platform has not published which countries are eligible for this job.
You apply on Alignerr, Labelbox's expert network: create a profile, complete an AI-led interview and skills assessment, then get matched to projects in your field.
Official posting: https://www.alignerr.com/jobs/09f63e2e-bd4a-4140-b39f-e6c9f04a0fbc
Last checked on October 8, 2026.
This freelance contract is for PhD-level mathematicians who will evaluate and improve how AI systems handle mathematical reasoning. The work covers writing and reviewing advanced problems, checking AI-generated proofs and calculations, and organizing mathematical content for training datasets. It suits holders of a doctorate in mathematics or a closely related field who can work independently and remotely on their own schedule.
This remote, hourly contract role asks mathematicians with a Master's or PhD to write, solve and review advanced problems, and to evaluate the mathematical reasoning produced by AI models. It suits researchers who are strong in algebra, calculus, statistics or discrete mathematics and who can work independently on their own schedule.
This role is designed for expert and experienced biologists to evaluate and rate responses generated by AI models in the field of biology. You will be tasked with writing research problems, evaluating experimental protocols, and identifying gaps between theoretically correct answers and their practical viability in the laboratory.
Posted September 15, 2026
Mercor is looking for life, physical and social science researchers to evaluate and rate work generated by AI models. Your role will involve designing research problems, rating the analysis produced by AI systems, and identifying methodological gaps, using your scientific expertise to establish evaluation criteria.
Posted September 15, 2026
A drug discovery scientist will design realistic preclinical tasks and evaluate how well frontier AI models perform them, grading responses against professional standards. The role involves creating scenarios based on real workflows, running them through AI systems, and providing detailed feedback on whether the models correctly conduct SAR analysis, DMPK interpretation, screening triage, and other core discovery work.
This role involves designing realistic experimental biology tasks and evaluating how frontier AI models perform on benchmark scientific challenges. You'll create scenarios from your own laboratory practice, run them through AI systems, and grade the AI's output against professional standards to help train models on hands-on experimental work.
