Remote Conservation Scientist for AI Training & Evaluation

Alignerr; Phoenix (AZ); On-site; USD 55,000 - 83,000; Full time

Benefits offered by this job

Autonomy

Variety of projects

Global collaboration

Job summary

Alignerr is seeking a Natural Resource Conservation Scientist to guide AI training in conservation science, land management, and ecosystem decision-making. You will evaluate AI content and provide structured feedback to ensure scientific accuracy and real-world applicability, influencing how AI understands environmental science.

Join a fully remote, task-based contract with flexible hours (10-40 hours/week) and opportunities for ongoing collaboration across global research labs.

Qualifications

• 3+ years of professional experience in natural resource conservation or environmental science.
• Strong foundational knowledge of ecosystems, land management, and conservation principles.
• Able to critically evaluate scientific reasoning and applied conservation recommendations.
• Comfortable reviewing structured written content and delivering detailed, constructive feedback.
• Self-motivated and reliable when working independently on task-based projects.

Responsibilities

• Review conservation science questions and scenarios used in AI training datasets.
• Evaluate the scientific accuracy of AI-generated content covering land use, ecosystems, soil health, water systems, and biodiversity.
• Assess whether AI-generated recommendations reflect real-world conservation practices and standards.
• Provide clear, structured feedback to improve AI scientific reasoning and output quality.
• Work independently and asynchronously on your own schedule.

Skills

Environmental science

AI training evaluation

Critical evaluation

Independent work

Education

Master's degree in Natural Resources

PhD in Natural Resources

Job description

Alignerr is seeking a Natural Resource Conservation Scientist to guide AI training in conservation science, land management, and ecosystem decision-making. You will evaluate AI content and provide structured feedback to ensure scientific accuracy and real-world applicability, influencing how AI understands environmental science.

Join a fully remote, task-based contract with flexible hours (10-40 hours/week) and opportunities for ongoing collaboration across global research labs.