Natural Resource Conservation Scientist (AI Training)
About The Role
Your field expertise has real value beyond the field — and AI needs it now. We're looking for experienced natural resource conservation scientists to help evaluate and improve AI systems trained on environmental science, land management, and conservation decision-making. This is a fully remote, flexible contract role where your scientific knowledge directly shapes how AI understands and communicates complex conservation topics. If you care about getting environmental science right, this is your opportunity to make an impact at the frontier of 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 to train AI systems
Evaluate the scientific accuracy of AI-generated content covering land use, ecosystems, soil, water, and biodiversity
Assess whether AI recommendations reflect sound, real-world conservation practices
Provide clear, structured feedback to improve scientific reasoning and AI outputs
Work independently and asynchronously — on your schedule, at your pace
Who You Are
3+ years of professional experience in natural resource conservation, environmental science,
or a closely related field
Strong working knowledge of ecosystems, land management principles, and conservation frameworks
Able to critically evaluate scientific reasoning and applied recommendations with clarity
Comfortable reviewing structured written content and providing detailed, actionable feedback
Self-motivated and reliable when working independently on deadline-driven tasks
Nice to Have
Master's degree or PhD in Natural Resources, Environmental Science, or a related discipline
Hands-on fieldwork or applied conservation project experience
Familiarity with AI systems, content evaluation workflows, or scientific writing
Why Join Us
Meaningful work — your expertise helps ensure AI gets environmental science right
Fully remote and flexible — work from anywhere, on a schedule that suits you
Cutting-edge exposure — gain insight into how advanced AI language models are trained and evaluated
Autonomy — task-based structure gives you control over your workload
Global collaboration — connect with a network of subject matter experts across disciplines
Potential for ongoing work — robust contributors are considered for contract extensions and new projects