Mindrift
AI
ChemistwithPythonExperience-FreelanceAITrainer
Neural analysis suggests this role is
optimal for Entry candidates.
“Chemist with Python Experience - Freelance AI Trainer at Mindrift. Skills: Computational chemistry, Python, AI training. Design computational chemistry problems to challenge a frontier AI model. Ensure problems have an answer verifiable by code”
What You'll Achieve.
Design tasks that score within range; Achieve a pass rate in the 10–30% band for tasks
Industry & Context.
Design problems that genuinely require a specialized tool; Tune problem difficulty until agent succeeds in a small number of attempts; Calibrate tasks for specific pass rates
Project-based participation, Not permanent employment, Problems run inside a sealed Linux container, Programmatic judge grades the model's answer
What They're Looking For.
Must Have
Degree in Chemistry or related, 2+ years of research, applied, or teaching, Python proficiency for writing reference, Fluency with — or willingness to independently learn — at least one scriptable computational chemistry package: GROMACS, LAMMPS, PySCF, ORCA, xtb, CREST, Quantum ESPRESSO, phonopy, pymatgen, AutoDock Vina, Ability to design problems that genuinely require a specialized, written English (C1+)
Nice to Have
Experience with Python
What You'll Do.
Design computational chemistry problems to challenge a frontier AI model
Ensure problems have an answer verifiable by code
Ensure problems require a specialized tool
Write a Python reference solution
Supply input files and molecular or crystal structure definitions
Decide the numerical answer and tolerance for correctness
Test the problem against the model in batches
Tune problem difficulty
Rewrite molecular geometries
Tighten basis sets and convergence thresholds
Observe agent behavior in simulations
How You'll Work.
Team & Collaboration
Tasks go to a senior reviewer for feedback; Ensure task quality is high
Communication Scope
English proficiency (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 computational chemistry 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 GROMACS, PySCF, ORCA, Quantum ESPRESSO, AutoDock Vina, or others. RDKit-style cheminformatics dressed up around generic libraries 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 force fields, integrators, electronic-structure methods, basis sets, or pseudopotential workflows. * Write a Python reference solution, supply input files and molecular or crystal structure definitions where needed. * Decide the numerical answer and how close the model needs to get — with a domain-appropriate tolerance — 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 molecular geometries, tightening basis sets and convergence thresholds, and watching how the agents act. You'll learn how these agents cut corners, where a simulation stalls, where a self-consistent field cycle converges. This time compounds in two directio
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