[Hiring] Physics & Python Expert - Freelance AI Trainer @Mindrift

Role Description

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 physics problems to challenge a frontier AI model.
• The problem must have an answer verifiable by code and require a specialized tool like FEniCS, OpenFOAM, Meep, REBOUND, CAMB, or others.
• 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 physics models, integrators, Monte Carlo kernels, or PDE discretisations.
• Write a Python reference solution, supply input files and domain or initial condition 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 for 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 field configurations.
• Tightening initial conditions and solver parameters.
• Watching how the agents act.

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 electromagnetic, fluid, gravitational, and cosmological problems.

Qualifications

• Degree in Physics (Theoretical, Experimental, or Computational) or related field.
• 2+ years of research, applied, or teaching experience.
• Python proficiency for writing reference solutions.
• Fluency with — or strong willingness to independently learn — at least one scriptable physics package: FEniCS / DOLFINx, OpenFOAM, Meep, MPB, openEMS, Geant4, PYTHIA8, ROOT / PyROOT, WarpX, REBOUND, MESA, CAMB, CLASS, or bilby.
• Ability to design problems that genuinely require a specialized simulation tool.
• Strong written English (C1+).

No prior experience with the listed tools? You're still welcome to apply — as long as you're ready to get up to speed on your own and hit the ground running.

Requirements

• This opportunity is a good fit for physicians with experience in Python open to part-time, non-permanent projects.

Benefits

• For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements.
• Contributors can earn up to $35 per hour equivalent, depending on their level and pace of contribution.
• Compensation varies across projects depending on scope, complexity, and required expertise.
• Please note that other projects on the platform may offer different earning levels based on their requirements.