Environmental Science Expert (AI Training) About The Role What if your expertise in climate modeling, ecology, or sustainability could directly shape how AI reasons about the planet's most pressing challenges? We're looking for Environmental Science experts — Masters and PhD holders — to develop complex, real-world problems that train the next generation of cutting-edge AI models. This is a fully remote, flexible contract role. No prior AI experience needed — just deep domain knowledge and a passion for scientific rigor.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 10–40 hours/week

What You'll Do

• Design, solve, and review advanced environmental science problems grounded in real-world relevance
• Apply your expertise in climate modeling, ecology, sustainability, or related fields to construct challenging, nuanced problem statements
• Collaborate asynchronously with AI researchers and fellow domain experts to push the boundaries of AI reasoning
• Ensure scientific accuracy, clarity, and depth across all deliverables
• Use Python or R where relevant to support research-quality outputs

Who You Are

• Holder of a Master's or PhD in Environmental Science or a closely related discipline
• Deeply knowledgeable in at least one of: climate modeling, ecology, or sustainability science
• Comfortable coding in Python or R for research or analytical purposes
• Exceptionally clear in both written and verbal communication — you can explain complex concepts with precision
• Detail-oriented, rigorous, and self-directed when working independently
• Fluent in English

Nice to Have

• Prior experience with data annotation, data quality assurance, or AI evaluation workflows
• Background in interdisciplinary environmental research spanning multiple subfields
• Familiarity with AI tools or large language model outputs as an end user

Why Join Us

• Work on cutting-edge AI projects alongside leading research labs and AI teams
• Fully remote and flexible — work when and where it suits you
• Freelance autonomy with the structure of meaningful, expert-level work
• Make a direct, tangible impact on how AI understands and reasons about climate and environmental science
• Potential for ongoing work and contract extension as new projects launch