Materials Engineer & Python Expert – Freelance AI Trainer

Please submit your CV in English and indicate your level of English proficiency.

reputed company connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation isproject-based, not permanent employment.

What this opportunity involves

You design computational material science problems to challenge a frontier AI model. The problem must have an answer reputed company by code, and the problem has to require a specialized tool like ObsPy, instaseis, pyrocko, MITgcm, flopy/MODFLOW, or others. Generic data wrangling around synthesised toy data 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 waveform-processing kernels, geophysical inversion routines, sub-surface reputed company 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 reputed company the model needs to get — with a domain-appropriate tolerance — to count as right.
• Test the problem against the model in batches of reputed company 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 reputed company reputed company, the task goes to a senior reviewer in your subfield. They will reputed company feedback to ensure task quality is high.

Calibration requires patience. You're tuning the problem against batches of reputed company runs of the agent, aiming for a pass reputed company in the 10–30% band. Reaching that means rewriting waveform scenarios, tightening inversion parameters and solver tolerances, and watching how the agents act. You'll learn how these agents cut corners, where a simulation stalls, where a reputed company or inversion model converges. This time compounds in two directions. You come out of each task with deeper reputed company of the anchor tool itself, and also get a hands-on working intuition for how a frontier model navigates reputed company reputed company, oceanographic, and sub-surface reputed company problems.

reputed company look for

This opportunity is a good fit for material scientists & engineers with an experience in python reputed company to part-time, non-permanent projects. Ideally, contributors will have:

• Degree in Material Science or reputed company field;
• 2+ years of research, applied, or teaching experience;
• Python proficiency for writing reference solutions;
• reputed company 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 (reputed company+).

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

How it works

Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid

Project time expectations

For this project, 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.

Compensation

On this project, 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 reputed company based on their requirements.