Natural Resource Conservation Scientist

Alignerr Corp.

United States

Remote

AUD 55.000 - 124.000

Teilzeit

Vor 2 Tagen
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Benefits dieser Stelle

Remote work
Flexible schedule

Zusammenfassung

Alignerr seeks experienced natural resource conservation scientists to shape how AI understands ecosystems, land management, and environmental decision-making. The role involves reviewing AI training content and improving how conservation science is represented in AI tools.

Ideal candidates have 3+ years in natural resource conservation and strong knowledge of ecosystems. Remote, flexible, and task-based with 10–40 hours per week, offering autonomy and potential ongoing work.

Qualifikationen

  • 3+ years of professional experience in natural resource conservation.
  • Strong working knowledge of ecosystems, conservation principles, and applied land management.
  • Able to critically evaluate scientific reasoning and applied recommendations with confidence.
  • Comfortable reviewing structured written content and delivering detailed, actionable feedback.

Aufgaben

  • Review conservation science questions, scenarios, and content used in AI training datasets.
  • Evaluate the scientific accuracy of AI-generated material covering land use, ecosystems, soil science, water systems, and biodiversity.
  • Assess whether AI recommendations align with established, real-world conservation practices.
  • Provide clear, structured feedback that improves scientific reasoning in AI outputs.
  • Work independently and asynchronously — on a schedule that fits your life.

Kenntnisse

Conservation science
Ecosystems knowledge
Critical reasoning
Feedback delivery
Independent work

Ausbildung

Master's degree or PhD in Natural Resources or related field

Jobbeschreibung

Natural Resource Conservation Scientist (AI Training)

About The Role

Your field expertise has real power — and not just in the field. We're looking for experienced natural resource conservation scientists to help shape how AI understands ecosystems, land management, and environmental decision-making.

As AI becomes increasingly embedded in scientific research and policy, the accuracy of its outputs matters enormously. That's where you come in. You'll work directly with AI training content, reviewing and improving how these systems reason about conservation science — ensuring the next generation of AI tools reflects real-world expertise.

  • 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 content used in AI training datasets
  • Evaluate the scientific accuracy of AI-generated material covering land use, ecosystems, soil science, water systems, and biodiversity
  • Assess whether AI recommendations align with established, real-world conservation practices
  • Provide clear, structured feedback that improves scientific reasoning in AI outputs
  • 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 applied recommendations with confidence
  • Comfortable reviewing structured written content and delivering detailed, actionable feedback
  • Self-motivated and reliable when working independently on 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 systems, content evaluation workflows, or data annotation
Why Join Us
  • Work on cutting-edge AI — contribute to projects at the frontier of environmental AI development
  • Fully remote and flexible — work from anywhere, on your own schedule
  • Your expertise drives impact — your scientific knowledge directly improves AI tools used in environmental contexts
  • 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
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