The work
You will create challenging questions about machine learning theory and applied mathematics, then review AI-generated answers. Your feedback will help improve how AI systems handle technical problem-solving.
The work covers optimization, generalization, model architectures, probabilistic modeling, statistical learning, and statistical inference.
- Write questions grounded in machine learning theory and applied mathematics.
- Check AI responses for technical accuracy, logical consistency, and sound reasoning.
- Assess explanations of optimization, generalization, model behavior, model architectures, probabilistic modeling, and statistical inference.
- Give clear feedback on how responses can improve.
What it pays and takes
This is ongoing, project-based contract work with a flexible, asynchronous schedule. It is designed to fit alongside research, teaching, postdoctoral work, or industry employment.
- Pay: Up to $75 per hour.
- Time: 20+ hours per week.
- Location: Remote and open to candidates in the United States.
- Language: Fluency in English.
- Education: Doctoral study, postdoctoral work, or graduate-level completion in machine learning or a closely related field.
- Knowledge: Strong machine learning theory, algorithmic analysis, and applied mathematics skills.
- Knowledge: Familiarity with optimization, probabilistic modeling, and statistical inference.
- Experience: You do not need prior AI evaluation or technical evaluation experience.
- Helpful backgrounds include statistics, computer science, artificial intelligence, and research involving model behavior, statistical learning, or machine learning algorithms.