Climate AI Training Specialist — Remote Contract

Alignerr Corp.

Boston (MA)

Remote

USD 55,000 - 96,000

Part time

7 hours ago
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Job summary

Alignerr is seeking an environmental science specialist to design and evaluate real-world problems that train AI models to reason about climate, ecology, and sustainability. This fully remote contract role is designed for Masters and PhD‑level scientists who want to apply deep domain knowledge to meaningful AI training.

You will work asynchronously with AI researchers, deliver rigorous problem sets, and help ensure scientific clarity and precision in outputs.

Qualifications

  • Master's or PhD in Environmental Science, Climate Science, Ecology, or closely related field.
  • Strong working knowledge of climate modeling and ecological systems.
  • Proficient in Python or R for research or data analysis.

Responsibilities

  • Design and develop advanced, real-world environmental science problems spanning climate modeling, ecology, sustainability, and related fields
  • Solve and critically review complex problem sets to ensure scientific accuracy, depth, and rigor
  • Apply your domain expertise to help AI models reason more accurately about environmental systems
  • Collaborate asynchronously with AI researchers and fellow domain experts to refine and improve AI outputs
  • Ensure all deliverables meet high standards of scientific clarity and precision

Skills

Climate modeling
Ecological systems
Sustainability science
Python
R
Scientific communication

Education

Master's or PhD in Environmental Science

Tools

Python
R

Job description

Alignerr is seeking an environmental science specialist to design and evaluate real-world problems that train AI models to reason about climate, ecology, and sustainability. This fully remote contract role is designed for Masters and PhD‑level scientists who want to apply deep domain knowledge to meaningful AI training.

You will work asynchronously with AI researchers, deliver rigorous problem sets, and help ensure scientific clarity and precision in outputs.

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