Natural Resource Conservation Scientist

Alignerr Corp.; Miami (FL); Remote; USD 55,000 - 110,000; Part time

Job summary

Alignerr, a labelbox-powered organization, is seeking an experienced natural resource conservation scientist to help train AI on conservation, land management, and environmental decision-making. This is a fully remote contract role with flexible hours and 10–40 hours per week.

You will review datasets, evaluate AI-generated content for ecological accuracy, and provide structured feedback to improve model reasoning. Work independently and asynchronously from anywhere in the world.

Qualifications

• 3+ years of professional experience in natural resource conservation, land management, or environmental science.
• Strong working knowledge of ecosystems, conservation principles, and applied land management.
• Able to critically evaluate scientific reasoning and identify errors or gaps in applied recommendations.
• Self-motivated and reliable in a remote, asynchronous work environment.

Responsibilities

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

Skills

NR conservation experience

Ecosystems knowledge

Critical evaluation

Remote work capability

Education

Master's or PhD in Natural Resources or related field

Job description

Natural Resource Conservation Scientist (AI Training)

Your field expertise has real power beyond the landscape — it can shape how AI understands and communicates environmental science. We're looking for experienced natural resource conservation scientists to help evaluate and improve AI systems trained on conservation, land management, and environmental decision-making.

This is a fully remote, flexible contract role where your scientific knowledge directly influences how the next generation of AI models reasons about the natural world.

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

Who You Are

• 3+ years of professional experience in natural resource conservation, land management, or environmental science
• Strong working knowledge of ecosystems, conservation principles, and applied land management
• Able to critically evaluate scientific reasoning and identify errors or gaps in applied recommendations
• Comfortable reviewing structured written content and delivering detailed, actionable feedback
• Self‑motivated and reliable in a remote, asynchronous work environment

Nice to Have

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

Why Join Us

• Meaningful impact: Your expertise helps ensure AI gets environmental science right — at scale
• Cutting‑edge work: Gain hands‑on exposure to advanced large language models (LLMs) and how they're trained
• Full flexibility: Work remotely on your own schedule, as much or as little as your availability allows
• Freelance autonomy: No micromanagement — you own your workflow
• Global collaboration: Join a community of subject‑matter experts from around the world
• Ongoing opportunity: Strong contributors are considered for contract extensions and future projects