Environmental Management Scientist (AI Training)

Alignerr Corp.; City of Edinburgh; Remote; GBP 34,000 - 69,000; Part time

Benefits offered by this job

Flexible hours

Remote work

Job summary

Alignerr Corp. is seeking environmental management professionals to shape how AI understands sustainability, conservation, and environmental decision-making. You will review AI-driven scenarios and provide structured feedback on AI reasoning related to land-use and resource planning.

The role is remote, hourly/task-based, with a commitment of 10–40 hours per week. Ideal for self-motivated individuals with 3+ years in the field and a Master’s-level qualification. AI familiarity is a plus.

Qualifications

• 3+ years of experience in environmental management or conservation.
• Strong working knowledge of sustainability frameworks, environmental planning, and impact assessment.
• Able to critically evaluate written environmental analyses with a practiced eye.
• Comfortable providing detailed, structured written feedback.
• Self-motivated and reliable — you can manage your time and meet deadlines independently.

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 outputs and real-world environmental practice.
• Provide clear, structured feedback to improve the accuracy and applicability of AI responses.
• Work independently and asynchronously to complete task-based assignments on your own schedule.

Skills

Sustainability frameworks

Environmental planning

Impact assessment

Critical feedback

Education

Master's degree in Environmental Management or related

Job description

About The Role

We're looking for environmental management professionals to help shape how AI understands sustainability, conservation, and environmental decision-making. Your real-world expertise will directly influence how cutting-edge AI systems reason about land-use planning, impact mitigation, and resource management — work that matters well beyond the screen.

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

Who You Are

• 3+ years of experience in environmental management, conservation, or a closely related field
• Strong working knowledge of sustainability frameworks, environmental planning, and impact assessment
• Able to critically evaluate written environmental analyses with a practiced eye
• Comfortable providing detailed, structured written feedback
• Self-motivated and reliable — you can manage your time and meet deadlines independently

Nice to Have

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

Why Join Us

• Work on meaningful AI projects — your environmental expertise directly improves how AI handles real-world sustainability challenges
• Fully remote and flexible — work on your own schedule, wherever you are
• Exposure to cutting-edge AI — gain rare insight into how large language models are trained and evaluated
• Autonomy and variety — no two days look the same; engage with diverse environmental scenarios and topics
• Potential for ongoing work — strong contributors are considered for contract extensions and future projects
• Global collaboration — connect with a network of subject‑matter experts across disciplines and regions