About The Role We're looking for experienced 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 topics on the planet. 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 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 structured, detailed feedback to improve the clarity, 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, environmental planning principles, and impact assessment methodologies
Able to critically evaluate written environmental analyses and identify weaknesses or inaccuracies
Skilled at providing clear, structured written feedback
Self-motivated and comfortable working independently in a remote setting
Nice to Have
Master's degree in Environmental Management, Environmental Science, or a related discipline
Experience with environmental policy, regulatory compliance, or permitting frameworks
Familiarity with AI systems, content evaluation workflows, or data annotation
Why Join Us
Work on cutting-edge AI projects with top research labs and make a real impact on how AI handles environmental topics
Fully remote and flexible — work from anywhere, on your own schedule
Freelance perks: autonomy, variety, and collaboration with a global network of subject-matter experts
Gain exposure to advanced large language models (LLMs) and how they are trained and evaluated
Potential for ongoing work and contract extension based on performance