Earth Sciences AI Task Designer

OpenTrain AI, Inc.; United States; Remote; USD 47,000 - 87,000; Part time

Job summary

OpenTrain seeks an Earth Sciences AI Task Designer to convert authentic Earth-science workflows into reproducible terminal benchmark tasks and datasets. You will design environments with Python, R, Bash, or Julia, enabling rigorous evaluation of AI systems.

You will validate data formats, coordinates, and tolerances while documenting provenance and limitations. Remote contractor role with five-week duration and flexible hours.

Qualifications

• Advanced training in Earth Sciences or closely related field (doctorate/postdoc or equivalent).
• Strong programming skills and experience with scientific data processing and modeling.
• Proficiency in Linux/terminal environments and scientific workflows.

Responsibilities

• Translate Earth-science workflows into self-contained terminal benchmark tasks.
• Prepare scientific datasets and reproducible environments with appropriate libraries and tools.
• Create expert solutions using Python, R, Bash, Julia or related software.
• Define objective grading criteria, validate coordinates, units, timestamps, and numerical tolerances.
• Document data provenance, edge cases, and limitations.

Skills

Earth Sciences

Scientific programming

Python

Linux

Geospatial analysis

Education

Doctoral/postdoctoral in Earth Sciences

Tools

Python

R

Bash

Julia

Job description

About OpenTrain

OpenTrain is the centralized, open platform where AI training and data-labeling freelancers find work, consolidate opportunities across platforms, and build a unified AI training portfolio they control. We make specialized AI training work easier to track, apply for, and grow into a durable freelance career.

About this role

OpenTrain is recruiting an Earth Sciences AI Task Designer to create realistic, terminal-based scientific tasks used to evaluate AI systems. You will translate authentic Earth-science workflows into reproducible computational challenges involving environmental, climate, atmospheric, geospatial, geological, hydrological, or oceanographic data. The work combines scientific judgment, programming, dataset preparation, workflow debugging, and objective evaluation of technical outputs.

What you will do

You will translate Earth-science workflows into self-contained terminal benchmark tasks, prepare scientific datasets, and build reproducible computational environments with appropriate libraries and command-line tools. You will create expert solutions using Python, R, Bash, Julia, or related scientific software. Your work may involve geospatial analysis, time-series processing, numerical modeling, interpolation, forecasting, remote sensing, and environmental risk analysis. You will define objective grading criteria, validate coordinate systems, units, timestamps, missing-data handling, metadata, and numerical tolerances, and debug projection, dependency, performance, and numerical-stability issues. You will also document data provenance, expected outputs, edge cases, and limitations.

Required skills

Candidates should have advanced technical training in Earth Sciences or a closely related field, including doctoral, postdoctoral, or equivalent experience. Strong expertise in at least one area such as climate science, atmospheric science, geophysics, oceanography, geology, hydrology, remote sensing, or environmental modeling is required. You should have strong scientific programming skills and hands-on experience with scientific data processing, numerical modeling, geospatial analysis, environmental datasets, or time-series analysis. Comfort working independently in Linux or terminal-based environments and a strong understanding of scientific quality control, uncertainty, spatial and temporal data, and numerical accuracy are important. Experience with scientific libraries, geospatial tools, scientific data formats, automated testing, scientific benchmarking, or reproducible computational environments is valuable.

Schedule and compensation

This is a remote, five-week contractor assignment requiring at least 6 hours per day and a minimum of 40 hours per week, with 4 hours of overlap with Pacific Time. Compensation is $300 per approved task.

Why work with OpenTrain

OpenTrain gives freelancers one place to manage AI training opportunities instead of rebuilding proof of work on every platform. A stronger OpenTrain profile helps you show credible experience, discover roles that match your skills, and turn AI training and data-labeling work into a long-term portfolio.