Environmental Science Professional LLM Evaluator

You will help improve language models by creating prompts based on real environmental science work and reviewing the responses they produce. Your evaluations will focus on whether the content is accurate, relevant, and shows a sound understanding of professional tasks.

The work is remote and primarily asynchronous. You will work independently across research projects, with assignments available based on project needs.

• Write prompts using environmental science methods, terminology, and professional tasks.
• Evaluate large language model responses for accuracy, relevance, and domain understanding.
• Use knowledge from environmental science and related technical fields to review AI-generated content.
• Communicate clearly in written work while working independently.

What it pays and takes

This role is open to candidates in the United States who can work in English. Professional experience in environmental science or a related field is required.

• Pay: Up to $100 per hour, depending on the assigned project.
• Hours: 20 or more hours per week.
• Work arrangement: Remote, flexible, and primarily asynchronous.
• Language: Professional fluency in English.
• Experience: At least five years in conservation science, environmental science, soil or plant science, environmental engineering, geoscience, or geological technology.
• Useful background: Environmental science practice, health-related environmental science, soil science, plant science, geology, or related technical work.
• Skills: Knowledge of environmental science terminology, methods, and professional tasks; sound judgment when assessing AI responses; clear written communication.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training work is the human side of building artificial intelligence. People write examples and review model responses so AI systems can better handle real-world questions, tasks, and language. Specialized expertise matters because experienced professionals can judge whether an answer is accurate and useful in their field.