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Wildlife and Habitat Conservation Scientist

$30-55/hrRemoteFreelanceSTEM

About the Role

Your field knowledge of wildlife biology and habitat conservation is more valuable than ever — and not just in the field. We're looking for conservation scientists to help train and evaluate AI systems that reason about biodiversity, ecological health, and conservation strategy.

This is a fully remote, flexible contract role where your scientific expertise directly shapes how AI understands the natural world. No prior AI experience required.

  • Organization: Alignerr (Powered by Labelbox)
  • Type: Hourly / Task-based Contract
  • Location: Remote
  • Commitment: 10–40 hours/week

What You'll Do

  • Review AI-generated wildlife and habitat conservation scenarios for scientific accuracy
  • Assess the quality of ecological reasoning and proposed conservation strategies
  • Identify unrealistic assumptions, flawed methodologies, or misapplied conservation concepts
  • Provide clear, structured feedback that improves the ecological validity of AI outputs
  • Work independently and asynchronously — on your schedule, at your pace

Who You Are

  • 3+ years of experience in wildlife biology, ecology, habitat conservation, or a closely related field
  • Strong working knowledge of biodiversity principles and ecosystem management
  • Able to critically evaluate applied ecological reasoning presented in written form
  • Comfortable reading and reviewing structured scientific content
  • Detail-oriented, self-motivated, and reliable when working independently

Nice to Have

  • Graduate degree in Ecology, Wildlife Biology, Conservation Science, or a related discipline
  • Hands-on field research or conservation program experience
  • Familiarity with AI systems, content evaluation, or scientific annotation workflows

Why Join Us

  • Meaningful impact — your expertise helps AI reason responsibly about conservation and the natural world
  • Fully remote and flexible — work from anywhere, on a schedule that fits your life
  • Cutting-edge work — gain direct exposure to how large language models are trained and evaluated
  • Autonomy — task-based structure means you're in control of your workflow
  • Global collaboration — connect with a diverse, expert community of scientists and researchers
  • Ongoing opportunity — strong contributors are considered for contract extension and future projects