This is not a traditional job — you'll draw on your hands-on experience in pure or applied mathematics to evaluate AI-generated content and provide feedback that helps AI reason like a practicing mathematician.

This is an ongoing, project-based opportunity you can take on alongside your current role.

• Use your domain expertise to create expert-level mathematics problems and scenarios grounded in real proof, formalization, and computational workflows.
• Review and evaluate AI-generated responses for technical accuracy, rigor, and alignment with how the work is actually done.
• Provide structured written feedback to help improve AI model performance.

Ideal candidates meet all three of the following:

• Research experience — first-author publications and the ability to formalize proofs that AI models fail on.

• Degree — PhD in Mathematics (pure or applied).

• Sub-domain depth — demonstrated expertise in one of the following areas:

  • Proof and formal methods (Lean, Coq, Isabelle).

  • Symbolic computation (SageMath, Mathematica), optimization, and numerical analysis.

  • A core subfield such as algebra, topology, number theory, or combinatorics.

Candidates who meet at least 2 of the 3 qualifications above are also encouraged to apply.

Additional qualifications (not required, but strengthen your application)

• Proficiency with theorem provers and symbolic computation software.

• Experience formalizing proofs or working on problems at the edge of what current AI models can handle.

Required for all applicants

• Must have Indian work authorization.

• Strong written communication and attention to detail.

• Ability to explain complex mathematical concepts clearly.

• Ability to work independently in a remote, asynchronous environment.

Work arrangement: Fully remote

Eligible countries: India

• Depending on the project.