Mathematician Talent Network

AI Training & Evaluation • Independent Contractor • Remote • Weekly Payouts

About Mercor’s talent network

Join our Mathematician Expert Network to connect with leading AI labs and companies seeking your expertise. This is an open application for future contract opportunities that match your background and interests.

Once you complete your profile and pass our AI interview, you'll be eligible for relevant projects as they become available. We match experts to opportunities on a rolling basis.

About Mercor projects

Experts in our network contribute to

• Training and evaluating AI models in Mathematics

• Creating tasks and deliverables based on real-world scenarios

• Providing domain-specific feedback to advance frontier AI research

Projects vary in scope and duration, with typical commitments ranging from 15-30 hours per week.

What we're looking for

• Professional experience in statistical analysis & modeling, mathematical proof & theory, computational mathematics

• Strong communication skills

• Ability to work independently in a remote environment

How it works

This is not a specific job posting. By applying, you're joining our Mathematician talent network.

• Apply once: Complete your profile by uploading your resume and confirming your work location.

• Get verified: We review your credentials and approve qualified experts.

• Stay connected: When projects need Mathematics expertise, we match you to opportunities based on your expertise and project needs.

• Start working: Be invited to interview for opportunities that align with your schedule and interests. You will earn competitive rates while working remotely on your own schedule.

Details

• Pay: $60 to $80 per hour (part-time)
• Commitment: Flexible • remote
• Eligible locations: United States
• Platform: Mercor (weekly payouts via Stripe or Wise)

Submit your application via the link below. Qualified candidates move through Mercor's short AI interview and selection process. Projects can be extended, shortened, or concluded early depending on needs and performance.