Natural Resource Conservation Scientist

Alignerr; United States; Remote; GBP 30,000 - 76,000; Part time

Benefits offered by this job

Autonomy

Global collaboration

Flexible schedule

Job summary

Alignerr is seeking experienced natural resource conservation scientists to shape how AI understands environmental science, land management, and conservation decision-making. This fully remote, flexible contract role offers you the chance to contribute to cutting-edge AI development on your own schedule.

You will review real-world scenarios, evaluate AI-generated content for accuracy across ecosystems, soil, water and biodiversity, and provide structured feedback to improve AI scientific

Qualifications

• 3+ years of professional experience in natural resource conservation, environmental science, or a closely related field.
• Foundational knowledge of ecosystems, land management strategies, and conservation principles.
• Ability to critically evaluate scientific reasoning and applied conservation recommendations.
• Ability to review structured content and provide detailed feedback.
• Self-motivated and reliable for remote independent work.

Responsibilities

• Review conservation science questions and real-world scenarios used in AI training datasets
• Evaluate scientific accuracy of AI-generated content on land use, ecosystems, soil, water, and biodiversity
• Assess whether AI outputs reflect sound conservation practices and principles
• Provide clear, structured feedback to improve AI scientific reasoning and recommendations
• Work independently and asynchronously to complete task-based assignments on your own schedule

Skills

Conservation experience

Ecosystems knowledge

Critical thinking

Technical writing

Education

Masters in Natural Resources

PhD in Environmental Science

Job description

Natural Resource Conservation Scientist (AI Training)

About The Role

We're looking for experienced natural resource conservation scientists to help shape how AI understands environmental science, land management, and conservation decision-making. Your expertise will directly influence the accuracy and reliability of AI systems used by researchers, policymakers, and practitioners worldwide.

This is a fully remote, flexible contract role — work on your own schedule while contributing to cutting-edge AI development.

• Organization: Alignerr (Powered by Labelbox)
• Type: Hourly / Task-based Contract
• Location: Remote
• Commitment: 10–40 hours/week

What You'll Do

• Review conservation science questions and real-world scenarios used in AI training datasets
• Evaluate the scientific accuracy of AI-generated content covering land use, ecosystems, soil, water, and biodiversity
• Assess whether AI outputs reflect sound, real-world conservation practices and principles
• Provide clear, structured feedback to improve AI scientific reasoning and recommendations
• Work independently and asynchronously to complete task-based assignments on your own schedule

Who You Are

• 3+ years of professional experience in natural resource conservation, environmental science, or a closely related field
• Strong foundational knowledge of ecosystems, land management strategies, and conservation principles
• Able to critically evaluate scientific reasoning and applied conservation recommendations
• Comfortable reviewing structured written content and providing detailed, actionable feedback
• Self-motivated and reliable when working independently in a remote environment

Nice to Have

• Master's degree or PhD in Natural Resources, Environmental Science, Ecology, or a related discipline
• Hands-on fieldwork or applied conservation project experience
• Familiarity with AI systems, content evaluation workflows, or data annotation

Why Join Us

• Work on cutting-edge AI projects that are shaping the future of environmental science applications
• Fully remote and flexible — design your own schedule around your life
• Freelance perks: autonomy, variety, and collaboration with experts across the globe
• Contribute to meaningful work that helps AI get environmental science right
• Potential for ongoing work and contract extension based on performance