Ecology AI Trainer

Ecology AI Trainer

Job Summary:

Join our customer's team as an Ecology AI Trainer to help shape the future of artificial intelligence in the ecological domain. In this highly collaborative and intellectually stimulating role, you will leverage your ecological expertise to rephrase complex domain-specific questions and design assessment rubrics that ensure AI models deliver accurate and insightful responses. This is an ideal opportunity for candidates who excel at translating scientific concepts into clear, structured, and actionable content.

Key Responsibilities:

• Rephrase and clarify challenging ecology-related questions to optimize them for AI training.
• Develop detailed rubrics to assess AI-generated answers for scientific accuracy, clarity, and depth of analysis.
• Review and provide constructive feedback on the ecological quality of AI-generated content.
• Collaborate with the customer's team to maintain consistency and clarity in large-scale training data.
• Utilize analytical thinking to identify gaps or ambiguities in training materials.
• Apply instructional design principles to create structured ecological assessments and guidelines.
• Maintain high standards of written and verbal communication in all documentation and reviews.

Required Skills and Qualifications:

• Bachelor’s or Master’s degree in Ecology, Environmental Science, or a closely related field.
• Demonstrated ecological expertise, with strong understanding of major ecological principles and terminology.
• Exceptional written and verbal communication skills, including excellent grammar and syntax.
• Experience with technical writing or instructional design in scientific contexts.
• Sharp analytical thinking and attention to detail for evaluating scientific accuracy.
• Native or advanced proficiency in English.
• Commitment of 10 hours per week with flexibility for asynchronous collaboration.

Preferred Qualifications:

• Experience training or mentoring others in ecology or related sciences.
• Background in developing educational content or learning assessments.
• Familiarity with AI, machine learning concepts, or data annotation in ecological applications.