About the Role
We're looking for environmental management professionals to help shape how AI understands sustainability, land-use planning, and environmental decision-making. Your real-world expertise will directly influence the quality and accuracy of AI systems tackling some of the most important challenges of our time.
This is a fully remote, flexible contract role — work on your own schedule and apply your knowledge in an exciting new frontier.
- Organization: Alignerr (Powered by Labelbox)
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Review and evaluate AI-generated environmental management scenarios, analyses, and recommendations
- Assess the quality of AI reasoning related to sustainability frameworks, impact mitigation, and resource planning
- Identify gaps between theoretical environmental models and real-world practice
- Provide clear, structured feedback to improve the accuracy and applicability of AI outputs
- Work independently and asynchronously to complete task-based assignments on your own schedule
Who You Are
- 3+ years of hands-on experience in environmental management, conservation, or a closely related field
- Strong working knowledge of sustainability frameworks and environmental planning principles
- Able to critically evaluate written environmental analyses for accuracy, completeness, and practical relevance
- Comfortable providing detailed, structured written feedback
- Self-motivated and reliable when working independently
- No prior AI experience required
Nice to Have
- Master's degree in Environmental Management, Environmental Science, or a related discipline
- Experience with environmental policy, regulatory frameworks, or compliance
- Familiarity with AI systems or content evaluation workflows
Why Join Us
- Work on cutting-edge AI projects with top research labs
- Fully remote and flexible — work on your own schedule, from anywhere
- Freelance perks: autonomy, variety, and global collaboration
- Contribute to meaningful work that improves how AI addresses real environmental challenges
- Exposure to advanced large language models (LLMs) and how they're trained
- Potential for ongoing work and contract extension