Forestry and Land Management Scientist (AI Training)
- Vancouver, British Columbia, Canada
- Télétravail
- Publié 12 sept. 2026
- 1 poste
30 $ US–55 $ US / heure
Ouvre un site externe
- Type d’emploi
- Contrat
- Niveau d’expérience
- Intermédiaire · 2+ ans
- Formation minimale
- Baccalauréat
- Postuler avant le
- 11 oct. 2026
- Langue de l’offre
- anglais
- Heures de travail
- 40 heures par semaine
- Exigences de lieu
- Country, Vancouver, British Columbia, Canada
- Niveau d’expérience
- Mid-Senior level
Résumé du poste
Review and assess AI-generated forestry and land management scenarios for scientific accuracy and practical soundness. Provide structured expert feedback to improve AI reasoning regarding forest health, sustainability, and ecosystem management.
Détails du poste
About The Role We're looking for experienced forestry and land management scientists to help shape the next generation of AI. Your field expertise will directly influence how AI systems understand, reason about, and communicate sustainable forestry and land-use practices — making a real-world impact on how this technology is used in environmental decision-making. Organization: Alignerr (Powered by Labelbox) Type: Hourly / Task-Based Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Review AI-generated forestry and land management scenarios for scientific accuracy and practical soundness Assess content related to forest health, land use, sustainability, and ecosystem management Identify errors, oversimplifications, or flawed reasoning in AI-generated recommendations Provide structured, expert feedback to improve how AI models reason through applied environmental problems Work independently and asynchronously on your own schedule Who You Are 3+ years of hands-on experience in forestry, land management, or a closely related field Strong working knowledge of forest ecosystems, silviculture, and sustainable land-use practices Able to critically evaluate applied environmental decision-making scenarios Comfortable reading and reviewing written technical content Self-motivated and reliable — no prior AI experience required Nice to Have Degree in Forestry, Natural Resources, Environmental Science, or a related discipline Experience with land-use planning, conservation programs, or regulatory frameworks 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 Freelance perks: autonomy, variety, and global collaboration Contribute to meaningful work that ensures AI gets environmental science right Potential for ongoing work and contract extension
Ce que vous ferez
Review and assess AI-generated forestry and land management scenarios for scientific accuracy and practical soundness. Provide structured expert feedback to improve AI reasoning regarding forest health, sustainability, and ecosystem management.
Exigences
Requires 3+ years of hands-on experience in forestry or land management with strong knowledge of silviculture and sustainable practices. Candidates must be able to critically evaluate technical content and work independently in an asynchronous environment.
Avantages
• Autonomy • Variety • Global collaboration • Flexible schedule
Compétences indiquées
- Technical · Souhaitée
- Sens de l’organisation · Souhaitée
- Training · Souhaitée
- Collaboration · Souhaitée
- Health · Souhaitée
- Planning · Souhaitée
- management · Souhaitée
- Decision Making · Souhaitée
- Accuracy · Souhaitée
- Reliable · Souhaitée
- Flexible · Souhaitée
- discipline · Souhaitée
Autres compétences pertinentes
Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.
- Forestry
- Land Management
- Silviculture
- Sustainable Land-Use Practices
- Forest Ecosystems
- Environmental Decision-Making
- Technical Content Review
- Ecosystem Management
- Conservation Programs
- Regulatory Frameworks
- Content Evaluation
Domaines d’emploi
- Science & Research
- Environmental & Sustainability
- Technology
- Agriculture
- Data & Analytics
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