About the Role
Your expertise in natural resource conservation doesn't just belong in the field — it belongs at the frontier of AI development. We're looking for experienced conservation and environmental scientists to help evaluate and improve AI systems trained on environmental science, land management, and conservation decision-making.
Your scientific knowledge will directly shape how AI understands and communicates complex conservation topics — helping ensure these systems are accurate, responsible, and grounded in real-world practice.
- Organization: Alignerr (Powered by Labelbox)
- Type: Hourly / Task-Based Contract
- Location: Fully 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 science, hydrology, and biodiversity
- Assess whether AI-generated recommendations reflect current, real-world conservation practices and standards
- Provide clear, structured feedback to improve AI scientific reasoning and output quality
- Work independently and asynchronously on a schedule that fits your life
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 flaws or gaps in AI-generated recommendations
- Comfortable reviewing structured written content and delivering detailed, actionable feedback
- Self-motivated and reliable when working independently on remote, task-based projects
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 workflows, or data annotation platforms
Why Join Us
- Work on cutting-edge AI — contribute to the development of advanced large language models (LLMs) alongside top research organizations
- Fully remote and flexible — work on your own schedule, from anywhere
- Make a real impact — your expertise helps ensure AI gets environmental science right
- Freelance perks — autonomy, variety, and collaboration with a global community of experts
- Potential for ongoing work — strong contributors are considered for contract extensions and future projects