Mindrift

AI

Mathematics&PythonExpert-FreelanceAITrainer

Elizabeth, New Jersey, United States PART TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Mathematics & Python Expert - Freelance AI Trainer at Mindrift. Skills: Mathematics, Python, AI Training. Design mathematics problems. Write Python reference solution”

What You'll Achieve.

Achieve pass rate in 10-30% band; Ensure task quality is high

Industry & Context.

AI
Problems you'll solve

Design mathematics problems to challenge AI; Tune problem difficulty; Analyze agent behavior

Eligibility Requirements

Work inside sealed Linux container, Programmatic judge grades 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, 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, Ability to design problems that genuinely require a specialized

What You'll Do.

Design mathematics problems

Write Python reference solution

Decide numerical answer

Test problem against model

Tune problem difficulty

Observe agent behavior

How You'll Work.

Team & Collaboration

Provide feedback to senior reviewer; Receive feedback from senior reviewer

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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