Mathematics Expert

Handshake
United States
about 1 month ago
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Role details

Contract type
Permanent contract
Employment type
Part-time (≤ 32 hours)
Compensation
$156,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Mathematica Isabelle Coq Formal Methods

Job description

  • 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
  • Complete tasks at your own pace with no set schedule or minimum hour requirement

Requirements

Handshake is looking for experienced mathematicians and research scientists to support AI research through flexible, part-time contract work. 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., 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, * 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 US 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

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Good distractions

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