About The Position

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. Contributors may design original computational mathematics problems that simulate real mathematical research workflows, create problems requiring Python programming to solve (using Numpy, SciPy, Sympy), ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks), develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis, base problems on real research challenges or practical applications from mathematical practice, verify solutions using Python with standard mathematical libraries, and document problem statements clearly and provide verified correct answers.

Requirements

  • Degree in Mathematics (Pure or Applied) or related fields
  • Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent
  • 2+ years of professional experience: applied, research, or teaching experience is applicable
  • Experience with numerical methods and symbolic computation
  • Ability to design problems that mirror real mathematical research workflows
  • Familiarity with computational complexity theory
  • Strong written English (C1+)

Responsibilities

  • Design original computational mathematics problems that simulate real mathematical research workflows
  • Create problems requiring Python programming to solve (using Numpy, SciPy, Sympy)
  • Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks)
  • Develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis
  • Base problems on real research challenges or practical applications from mathematical practice
  • Verify solutions using Python with standard mathematical libraries
  • Document problem statements clearly and provide verified correct answers
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