About the Role
We're looking for experienced soil and water conservation scientists to help shape how AI understands and communicates sustainable land and water management. Your scientific expertise will directly influence the accuracy and reliability of AI systems tackling some of the most important environmental challenges of our time.
This is a fully remote, flexible contract role — work on your own schedule while contributing to cutting-edge AI development.
- 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 real-world applicability
- Evaluate content covering erosion control, watershed management, soil health, and conservation planning
- Identify flawed assumptions, outdated practices, or impractical recommendations in AI outputs
- Provide clear, structured feedback that improves the scientific rigor and clarity of AI training data
- Work independently and asynchronously — no meetings required, no fixed schedule
Who You Are
- 3+ years of hands-on experience in soil science, hydrology, or conservation planning
- Strong foundational knowledge of soil processes, water systems, and conservation techniques
- Skilled at critically evaluating applied environmental science reasoning
- Comfortable reviewing and annotating technical written content
- Self-motivated and reliable — able to meet deadlines 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 software
- Prior exposure to AI content evaluation or data annotation workflows
Why Join Us
- Work on cutting-edge AI projects with top research labs — your expertise genuinely matters
- Fully remote and flexible — set your own hours and work from anywhere
- Freelance perks: autonomy, variety, and collaboration with a global expert community
- Gain firsthand exposure to advanced large language models (LLMs) and how they're trained
- Potential for ongoing work and contract extension as projects evolve