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

Role Description

This opportunity involves designing computational material science problems to challenge a frontier AI model. The problem must have an answer verifiable by code and require a specialized tool like ObsPy, instaseis, pyrocko, MITgcm, flopy/MODFLOW, or others. Generic data wrangling around synthesized toy data won't suffice. 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 waveform-processing kernels, geophysical inversion routines, sub-surface flow solvers, or community-validated data pipelines.
• Write a Python reference solution, supply input files and model or domain 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, tuning the problem against batches of parallel runs of the agent, aiming for a pass rate in the 10–30% band.
• Learn how these agents cut corners, where a simulation stalls, and where a flow or inversion model converges.

This time compounds in two directions: you come out of each task with deeper command of the anchor tool itself and a hands-on working intuition for how a frontier model navigates complex seismic, oceanographic, and sub-surface flow problems.

Qualifications

• Degree in Material Science 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 package: ObsPy, instaseis, pyrocko, MITgcm, xmitgcm, flopy / MODFLOW, or GeoPandas.
• Ability to design problems that genuinely require a specialized solver.
• 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 material scientists & engineers with experience in Python open to part-time, non-permanent projects.

Benefits

• Compensation: 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.

Project time expectations

• Tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements.
• This is an estimate, not a guaranteed workload, and applies only while the project is active.