- Title: Environmental Scientist (Remote)
- Engagement: Hourly contract (independent contractor)
- Rate: USD 62-120/hour
Job Summary
We are seeking an experienced Conservation Scientist to join our customer's team as an AI Trainer. In this remote role, you will apply your expertise in natural resource management to help train and refine AI systems designed to support sustainable land use, soil and water conservation, and environmental stewardship. Your field knowledge will ensure AI-driven tools reflect real-world conservation practices and sound ecological principles.
Key Responsibilities
- Collaborate with AI engineers and data scientists to train and improve machine learning models using conservation-focused datasets
- Apply principles of agronomy, forestry, soil science, and sustainable agriculture to guide AI development
- Review, design, and validate datasets representing best practices in soil and water conservation, erosion control, rangeland management, and watershed protection
- Provide subject matter expertise on conservation planning and sustainable land management strategies
- Evaluate AI outputs to ensure alignment with environmental regulations, conservation standards, and practical field applications
- Develop recommendations for AI-supported conservation initiatives such as crop rotation, reforestation, nutrient management, and land rehabilitation
- Communicate scientific insights clearly to both technical and non-technical stakeholders in written and verbal formats
Required Skills and Qualifications
- Proven experience as a Conservation Scientist, Resource Conservationist, Soil Conservationist, Land Reclamation Specialist, or similar role
- Strong background in soil, water, and land resource management
- Familiarity with conservation practices including contour plowing, terracing, crop rotation, erosion mitigation, and watershed management
- Experience advising farmers, ranchers, landowners, or agencies on sustainable land use strategies
- Excellent written and verbal communication skills
- Strong analytical skills with attention to detail in dataset validation and scientific review
- Ability to work effectively in a fully remote, cross-functional environment
Preferred Qualifications
- Experience contributing to AI, machine learning, or data-driven environmental initiatives
- Advanced degree in Environmental Science, Soil Science, Forestry, Agronomy, or a related field
- Background in conservation program development or collaboration with governmental or environmental organizations
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