Generation Asset Analyst, AI Training

As a Generation Asset Analyst supporting AI training, you will create expert data and evaluate AI-generated content. Your feedback will help AI better understand energy operations, plant performance, reliability, SCADA, production, and generation asset analysis.

You will work independently and asynchronously with AI research teams. Prior AI experience is not required.

• Create expert training data from your practical knowledge of energy operations and daily work tools.
• Review AI-generated responses for accuracy, relevance, and fit with real-world operations workflows.
• Give clear, detailed feedback based on plant performance, reliability, SCADA, production, or generation asset analysis.
• Use careful written reasoning to explain technical judgments.

What it pays and takes

This is project-based contract work for professionals with energy-industry experience. The opportunity is fully remote and ongoing, with a flexible, asynchronous schedule.

• Pay: Up to $85 per hour.
• Time: 20+ hours per week.
• Location: Open to candidates in the United States.
• Language: Fluent in English.
• Experience: At least two years in industrial operations, plant performance, energy asset management, or an equivalent energy-industry role.
• Relevant backgrounds include Plant Performance Engineer, Reliability Engineer, SCADA Engineer, Drilling or Production Engineer, or Generation Asset Analyst.
• Tools: Hands-on experience with at least one of AVEVA PI, WinCC, Oracle MDM, Power BI, or Bloomberg Terminal.
• Skills: Strong written communication, attention to detail, and the ability to work independently and asynchronously.
• Helpful experience includes interpreting operational data, assessing plant or asset performance, and explaining technical judgments clearly.

How it works

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

About AI training work

AI training is the human work behind artificial intelligence. People create examples, review model responses, and provide feedback so AI systems can produce more accurate and useful results; specialized experience matters because it helps make those examples and evaluations reliable.