Energy Project Estimator AI Evaluator

You will help improve AI systems by reviewing responses about energy project estimation, construction planning, solar design, and cost estimation. You will also create training examples based on real energy-industry workflows and professional judgment.

The work is independent, remote, and asynchronous. You will check technical answers for accuracy and relevance, then explain your judgment in clear written feedback.

• Evaluate AI-generated responses about energy project estimation, construction planning, solar design, and cost estimation.
• Create expert-level training data grounded in energy-industry workflows.
• Review technical responses and provide clear written feedback about their accuracy and relevance.
• Use practical knowledge of Bluebeam Revu, RSMeans, or Aurora Solar when assessing content.

What it pays and takes

This is ongoing, project-based contract work that can be done part time. The role is open to candidates in the United States and requires professional fluency in English.

• Pay: up to $85 per hour.
• Time: 20 or more hours per week.
• Work setup: fully remote, flexible, and asynchronous.
• Experience: at least two years in energy project estimation, pre-construction, solar design, or a comparable energy-industry role.
• Relevant backgrounds include estimator, project engineer, pre-construction manager, or solar design engineer.
• Tools: hands-on experience with at least one of Bluebeam Revu, RSMeans, or Aurora Solar.
• Skills: strong written communication and the ability to judge whether technical responses are accurate and relevant.
• No previous AI experience is required.

How it works

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

About AI training work

AI training work is the human side of building artificial intelligence. People review and write examples, rate model responses, and provide feedback so AI systems can produce more accurate and useful results.

OpenTrain is a free platform where people find AI training and data-labeling work, build a profile, and start applications across the industry.