Environmental Management Scientist (AI Training)

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 accuracy and quality of AI systems tackling some of the most complex environmental challenges of our time.

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, depth, 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 related field
• Strong working knowledge of sustainability frameworks, environmental planning, and impact assessment
• Able to critically evaluate written environmental analyses and identify where they fall short
• Comfortable providing detailed, structured written feedback
• Self-motivated and reliable — you can work independently and meet deadlines without close supervision

Nice to Have

• Master's degree in Environmental Management, Environmental Science, or a related field
• Experience with environmental policy, regulatory frameworks, or compliance
• Familiarity with AI systems, content evaluation, or annotation workflows

Why Join Us

• Work on cutting-edge AI projects with top research labs and a global team
• Fully remote and flexible — set your own hours and work from anywhere
• Freelance perks: autonomy, variety, and meaningful work that has real impact
• Contribute to AI systems that handle important real-world environmental topics
• Potential for ongoing work and contract extension

Organization

Alignerr (Powered by Labelbox)

Type

Hourly / Task-based Contract

Commitment

10–40 hours/week