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 integral 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