Natural Resource Conservation Scientist

Natural Resource Conservation Scientist (AI Training)About The RoleYour 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 ContractLocation: RemoteCommitment: 10–40 hours/weekWhat You'll DoReview conservation science questions, scenarios, and case studies used in AI training datasetsEvaluate the scientific accuracy of AI-generated content covering ecosystems, land use, soil health, water systems, and biodiversityAssess whether AI recommendations reflect real-world conservation practices and sound scientific reasoningProvide clear, structured feedback to improve the quality and reliability of AI outputsWork independently and asynchronously on your own scheduleWho You Are3+ years of professional experience in natural resource conservation, land management, or environmental scienceStrong working knowledge of ecosystems, conservation principles, and applied land managementAble to critically evaluate scientific reasoning and identify errors or gaps in applied recommendationsComfortable reviewing structured written content and delivering detailed, actionable feedbackSelf-motivated and reliable in a remote, asynchronous work environmentNice to HaveMaster's degree or PhD in Natural Resources, Environmental Science, Ecology, or a related fieldHands-on fieldwork or applied conservation project experienceFamiliarity with AI systems, content evaluation, or annotation workflowsWhy Join UsMeaningful impact: Your expertise helps ensure AI gets environmental science right — at scaleCutting-edge work: Gain hands-on exposure to advanced large language models (LLMs) and how they're trainedFull flexibility: Work remotely on your own schedule, as much or as little as your availability allowsFreelance autonomy: No micromanagement — you own your workflowGlobal collaboration: Join a community of subject-matter experts from around the worldOngoing opportunity: Strong contributors are considered for contract extensions and future projectsJ-18808-Ljbffr