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Soil and Water Conservation Scientist

Remote role Full-time Open position

Soil and Water Conservation Scientist (AI Training) About The Role We're looking for soil and water conservation scientists to help evaluate and improve AI systems trained on sustainable land and water management practices. Your scientific expertise will directly shape how AI understands, reasons about, and communicates complex conservation topics — making a real impact on the quality of environmental AI tools used worldwide.

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

What You'll Do

  • Review AI-generated soil and water conservation scenarios for scientific accuracy and practical soundness
  • Assess content related to erosion control, watershed management, and soil health
  • Identify flawed assumptions, oversimplifications, or impractical recommendations in AI outputs
  • Provide structured, expert feedback to improve scientific rigor, clarity, and real-world applicability
  • Work independently and asynchronously on your own schedule

Who You Are

  • 3+ years of hands-on experience in soil science, hydrology, or conservation planning
  • Strong working knowledge of soil processes, water systems, and conservation techniques
  • Able to critically evaluate applied environmental science reasoning and written technical content
  • Detail-oriented, self-motivated, and comfortable working remotely without close supervision

Nice to Have

  • Graduate degree in Soil Science, Hydrology, Environmental Science, or a related field
  • Experience with field assessments, GIS tools, or conservation planning platforms
  • Familiarity with AI systems, content evaluation, or annotation workflows

Why Join Us

  • Work on cutting-edge AI projects with top research labs and technology organizations
  • Fully remote and flexible — work when and where it suits you
  • Freelance perks: autonomy, variety, and collaboration with a global community of experts
  • Contribute to meaningful work that improves how AI handles real-world environmental science
  • Potential for ongoing work and contract extension

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