Earth Sciences Research Engineering Expert at Turing

Earth Sciences Research Engineering Expert | Remote | 4-week contractor assignment

Turing, an AI company working with leading AI labs, is seeking Earth Sciences experts to develop realistic, terminal-based scientific and computational tasks for a frontier AI training and evaluation initiative.

About the Role

You will design challenging scientific tasks involving climate science, atmospheric processes, geophysics, oceanography, geology, hydrology, remote sensing, and environmental modeling. You will build reproducible computational workflows that require AI agents to analyze scientific datasets, execute code, run simulations, troubleshoot technical issues, and generate objectively verifiable scientific outputs.

What You'll Do

• Design realistic, multi-step scientific tasks based on authentic Earth Sciences, climate, geospatial, environmental, and geophysical research workflows.
• Prepare and process scientific datasets involving climate, weather, atmospheric conditions, oceanography, geology, hydrology, satellite imagery, and environmental systems.
• Develop computational tasks involving geospatial analysis, time-series processing, numerical modeling, interpolation, forecasting, remote sensing, and environmental risk analysis.
• Build reproducible, terminal-based computational environments using scientific libraries, command-line tools, and appropriate dependencies.
• Develop expert reference solutions using Python, R, Bash, Julia, or domain-specific scientific software.
• Create automated tests and evaluation criteria to verify scientific correctness, numerical accuracy, and reproducibility.
• Validate coordinate reference systems, measurement units, timestamps, missing-data handling, uncertainty, and scientific assumptions.
• Troubleshoot technical issues involving geospatial projections, large datasets, software dependencies, and numerical stability.
• Document dataset sources, workflows, expected outputs, edge cases, and scientific limitations.

Requirements

• Ph.D., postdoctoral experience, or equivalent advanced technical experience in Earth Sciences, Climate Science, Atmospheric Science, Geophysics, Oceanography, Geology, Hydrology, Environmental Science, or a closely related discipline.
• Strong programming skills in Python, R, Bash, Julia, or another relevant scientific programming language.
• Hands-on experience working in Linux and terminal-based computational environments.
• Practical expertise in at least one major area: scientific data processing, numerical modeling, geospatial analysis, climate modeling, remote sensing, or environmental data analysis.
• Experience working with real-world scientific datasets, including geospatial, climate, atmospheric, oceanographic, geological, or hydrological data.
• Ability to independently develop, execute, debug, and validate reproducible scientific computational workflows.

Nice to Have

• Experience with scientific computing and geospatial libraries such as NumPy, pandas, SciPy, xarray, rasterio, GeoPandas, Cartopy, or GDAL.
• Familiarity with scientific data formats such as NetCDF, HDF5, GeoTIFF, shapefiles, and GRIB.
• Familiarity with Docker, Conda, Git, CI/CD pipelines, and automated testing frameworks.
• Experience with high-performance computing (HPC) environments or large-scale scientific datasets.
• Research software engineering experience, including developing scientific tools or reproducible research workflows.
• Publications, research contributions, or open-source development experience in Earth or Environmental Sciences.

Schedule and Terms

• Commitment: at least 4 hours per day, minimum 40 hours per week, with 4 hours of overlap with PST.
• Employment type: contractor assignment (no medical or paid leave).
• Contract duration: 4 weeks, with an expected start date next week.

Pay rate is not specified in the source listing.