Are you a natural resource or environmental scientist who wants to do something truly different with your expertise? We're looking for experienced conservation specialists to help evaluate and improve AI systems being trained on environmental science, land management, and conservation decision-making.
Your scientific knowledge will directly shape how AI understands ecosystems, interprets conservation data, and recommends land management strategies — making a real-world difference in how this technology serves the environment and the people who protect it.
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, scenarios, and datasets used in AI training
Evaluate the scientific accuracy of AI-generated content related to 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 scientific reasoning and AI outputs
Work independently and asynchronously — on your own schedule, from anywhere
Who You Are
3+ years of skilled experience in natural resource conservation, land management, or environmental science
Solid 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 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 experience
Familiarity with AI tools, content evaluation workflows, or scientific writing review
Why Join Us
Meaningful impact — your expertise helps ensure AI gets environmental science right
Fully remote and versatile — work when and where it suits you
Cutting-edge work — gain firsthand exposure to how advanced AI models are trained and improved
Autonomy — task-based structure means you control your workload
Global collaboration — work alongside experts from around the world
Potential for ongoing work — robust contributors are considered for contract extensions and future projects