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 quality and accuracy of AI systems tackling some of the planet's most pressing challenges.

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 and analyses
• Assess the quality of AI reasoning related to sustainability, impact mitigation, and resource planning
• Identify gaps between theoretical frameworks and real-world environmental practice
• Provide clear, structured feedback to improve AI accuracy and applicability
• Work independently and asynchronously to meet project milestones
  
  

Who You Are

• 3+ years of hands-on experience in environmental management, conservation, or a related field
• Strong command of sustainability frameworks, environmental planning, and impact assessment
• Able to critically evaluate written environmental analyses with precision
• Comfortable delivering detailed, structured feedback in written form
• Self-motivated and reliable in a remote, asynchronous work environment
  
  

Nice to Have

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

Why Join Us

• Work on cutting-edge AI projects with top research labs
• Fully remote and flexible — design your own schedule
• Freelance perks: autonomy, variety, and global collaboration
• Contribute to meaningful work that helps AI better understand environmental challenges
• Exposure to advanced large language models (LLMs) and how they are trained
• Potential for ongoing work and contract extension