Remote Forestry & Land Management AI Specialist

Alignerr Corp.; United States; A distancia; GBP 14.000 - 55.000; A tiempo parcial

Descripción de la vacante

Alignerr (Powered by Labelbox) is seeking experienced forestry and land management scientists to shape how AI understands sustainable forestry, land-use planning, and ecosystem management. You can work from anywhere on a remote, hourly/task-based contract.

Contribute by reviewing AI training datasets, assessing accuracy of forest health and land-use content, and providing structured feedback. Flexible schedule: 10–40 hours per week, with independent, asynchronous work.

Formación

• 3+ years hands-on experience in forestry, land management, or closely related field.
• Strong working knowledge of forest ecosystems, silviculture, and land management practices.
• Clear written communicator who can articulate feedback precisely and constructively.

Responsabilidades

• Review forestry and land management scenarios used in AI training datasets.
• Assess the accuracy of AI-generated content related to forest health, land use, and sustainability.
• Identify factual errors, oversimplifications, or flawed management recommendations.
• Provide clear, structured feedback to improve AI reasoning on applied environmental topics.
• Work independently and asynchronously — on your own schedule.

Conocimientos

Forestry experience

Land management

Critical evaluation

Written communication

Self-motivated remote work

Educación

Degree in Forestry, Natural Resources, Environmental Science, or related discipline

Descripción del empleo

Alignerr (Powered by Labelbox) is seeking experienced forestry and land management scientists to shape how AI understands sustainable forestry, land-use planning, and ecosystem management. You can work from anywhere on a remote, hourly/task-based contract.

Contribute by reviewing AI training datasets, assessing accuracy of forest health and land-use content, and providing structured feedback. Flexible schedule: 10–40 hours per week, with independent, asynchronous work.