Mindrift
AI
Mathematics&PythonExpert-FreelanceAITrainer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Mathematics & Python Expert - Freelance AI Trainer at Mindrift. Skills: Mathematics, Python, Specialized mathematical packages (Z3, cvc5, SageMath, Macaulay2, etc.). Design mathematics problems to challenge a frontier AI model. Ensure problems have an answer verifiable by code and require a specialized tool”
What You'll Achieve.
AI model success rate in the 10-30% band; High task quality
Industry & Context.
Designing challenging mathematics problems; Troubleshooting AI model performance issues; Adapting problems based on AI behavior
Problems run inside a sealed Linux container with the tool pre-installed, Programmatic judge grades the model's answer
What They're Looking For.
Must Have
Degree in Mathematics (Pure or Applied) or related, 2+ years of research, applied, or teaching, Python proficiency for writing reference, Ability to design problems that genuinely require a specialized tool, written English (C1+)
Nice to Have
Fluency with — or willingness to independently learn — at least one scriptable mathematical package: Z3, cvc5, Macaulay2, Singular, CasADi, IPOPT, SDPB, G6K, fpylll
What You'll Do.
Design mathematics problems to challenge a frontier AI model
Ensure problems have an answer verifiable by code and require a specialized tool
Write a Python reference solution
Supply input files where needed
Decide the numerical answer and acceptable tolerance
Test problems against the model in batches
Tune problem difficulty for a 10-30% success rate
Rewrite and re-tighten problems based on agent behavior
Ensure task quality is high through feedback and review
How You'll Work.
Team & Collaboration
Submit tasks to a senior reviewer for feedback
Communication Scope
Written English (C1+)
Full Job Description
_**Please submit your CV in English and indicate your level of English proficiency.**_ 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.** **What this opportunity involves** You design mathematics problems to challenge a frontier AI model. The problem must have an answer verifiable by code, and the problem has to require a specialized tool like Z3, cvc5, SageMath, Macaulay2, or others. NumPy or SymPy on their own won't cut it. Each problem runs inside a sealed Linux container with the tool pre-installed and a programmatic judge that grades the model's answer. As an expert author, you: • Pick an anchor tool and design a problem that hinges on its usage. • Write a Python reference solution, supply input files optionally where needed. • Decide the numerical answer and how close the model needs to get to count as right. • Test the problem against the model in batches of parallel attempts, tuning the problem difficulty until the agent only succeeds in a small number of attempts. • Once you're happy with the task, and it scores within range, the task goes to a senior reviewer in your subfield. They will provide feedback to ensure task quality is high. Calibration requires patience. You're tuning the problem against batches of parallel runs of the agent, aiming for a pass rate in the 10-30% band. Reaching that means rewriting, re-tightening, and watching how the agents act. You'll learn how these agents cut corners, where it stalls, where it converges. This time compounds in two directions. You come out of each task with deeper command of the anchor tool itself, and also get a hands on working intuition for how a frontier model navigates complex scientific problems. **What we look for** This opportunity is a good fit for mathematicians with an experience in python open to part-time, non-permanent projects. Ideally
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