Environmental Management Scientist (AI Training)

Alignerr; Municipio de Rincón de los Sauces; Remote; ARS 53,224,000 - 85,158,000; Part time

Benefits offered by this job

Autonomy

Variety

Global collaboration

Job summary

Alignerr Corp. is seeking environmental management professionals to shape AI understanding of sustainability and planning. This is a fully remote, hourly contract role with 10–40 hours per week, offering flexible scheduling and independent work.

You will review AI-generated environmental analyses, assess reasoning, and provide structured feedback to improve AI outputs while working asynchronously on-task.

Qualifications

• 3+ years of hands-on experience in environmental management, conservation, or a closely related field.
• Strong working knowledge of sustainability frameworks and environmental planning principles.
• Able to critically evaluate written environmental analyses for accuracy, completeness, and practical relevance.
• Comfortable providing detailed, structured written feedback.
• Self-motivated and reliable when working independently.
• No prior AI experience required.

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

Skills

Environmental management

Sustainability frameworks

Environmental planning

Written feedback

Independent work

Critical evaluation

Education

Master's degree in Environmental Management or related 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 tackling some of the most important challenges of our time.
This is a fully remote, flexible contract role — work on your own schedule and apply your knowledge in an exciting new frontier.

• Organization: Alignerr (Powered by Labelbox)
• Type: Hourly 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 clear, structured feedback to improve the 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 and environmental planning principles
• Able to critically evaluate written environmental analyses for accuracy, completeness, and practical relevance
• Comfortable providing detailed, structured written feedback
• Self-motivated and reliable when working independently
• No prior AI experience required
  

Nice to Have

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

Why Join Us

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