Environmental Management Scientist (AI Training)

Alignerr Corp.; Toronto; Remote; CAD 34,000 - 83,000; Part time

Job summary

Alignerr Corp. is seeking environmental management professionals to help shape AI understanding of sustainability, land-use planning, and environmental decision-making.

Your real-world expertise will influence AI systems used by researchers, policymakers, and practitioners worldwide, with fully remote, flexible hourly contracts and 10–40 hours per week. You will review AI-generated environmental analyses, assess sustainability frameworks, and deliver structured feedback to improve AI outputs

Qualifications

• 3+ years of hand-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 with a practiced eye
• Skilled at delivering detailed, structured, and constructive feedback
• Self-motivated and comfortable managing your own workload remotely

Responsibilities

• 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 approaches and real-world environmental practice
• Provide clear, structured feedback to improve the accuracy and applicability of AI outputs
• Work independently and asynchronously on your own schedule

Skills

Environmental management

Conservation

Sustainability frameworks

Impact assessment

Feedback delivery

Independent work

Education

Master's degree in Environmental Management

Bachelor's degree in Environmental field

Job description

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 used by researchers, policymakers, and practitioners worldwide.

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 used by researchers, policymakers, and practitioners worldwide.

This is a fully remote, flexible contract role where your knowledge genuinely matters - you're not just reviewing content, you're helping AI get environmental science right.

• 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 approaches and real-world environmental practice
• Provide clear, structured feedback to improve the accuracy and applicability of AI outputs
• Work independently and asynchronously on your own schedule

Who You Are

• 3+ years of hand-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 with a practiced eye
• Skilled at delivering detailed, structured, and constructive feedback
• Self-motivated and comfortable managing your own workload remotely

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, or data annotation workflows

Why Join Us

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