Environmental Specialist | Remote

Crossing Hurdles; New Zealand; On-site; NZD 90,000 - 130,000; Full time

Job summary

Crossing Hurdles seeks experts to design realistic earth-science tasks that push advanced AI models, with a focus on reproducible environments and robust evaluation criteria. Applicants will develop reference solutions and benchmarks for geospatial analyses, simulations, and forecasting.

The role requires hands-on Python expertise and deep knowledge in earth or environmental science, plus experience benchmarking AI systems on scientific tasks.

Qualifications

• Prior paid experience training, evaluating, benchmarking, or improving AI systems on scientific or technical tasks.
• Strong practical proficiency with Python.
• Deep expertise in at least one relevant earth or environmental-science specialization.
• Hands-on experience using computational methods for geospatial analysis, modeling, forecasting, remote sensing, statistics, or reproducible research.

Responsibilities

• Create realistic computational earth-science tasks that challenge advanced AI models.
• Develop task instructions, reproducible environments, reference solutions, and evaluation criteria.
• Evaluate model-generated code, geospatial analyses, simulations, forecasts, and technical deliverables.
• Identify issues involving coordinate systems, spatial or temporal data, model assumptions, uncertainty, numerical methods, or reproducibility.

Skills

Python

Geospatial analysis

Reproducible research

Model evaluation

Tools

GeoPandas

NumPy

Job description

• Create realistic computational earth-science tasks that challenge advanced AI models.
• Develop task instructions, reproducible environments, reference solutions, and evaluation criteria.
• Evaluate model-generated code, geospatial analyses, simulations, forecasts, and technical deliverables.
• Identify issues involving coordinate systems, spatial or temporal data, model assumptions, uncertainty, numerical methods, or reproducibility.

Requirements

• Prior paid experience training, evaluating, benchmarking, or improving AI systems on scientific or technical tasks.
• Strong practical proficiency with Python.
• Deep expertise in at least one relevant earth or environmental-science specialization.
• Hands-on experience using computational methods for geospatial analysis, modeling, simulation, forecasting, remote sensing, statistics, or reproducible research.