Completions Engineer AI Training Evaluator

This project involves creating expert training data and reviewing AI-generated content about drilling, completions, well planning, and energy data systems. You will work independently and provide clear feedback that helps AI systems better reflect real industry practices.

The project is described as drilling and completions AI evaluation, so review the duties and qualifications before applying.

• Create high-quality AI training data using professional knowledge of drilling, completions, and related energy operations.
• Evaluate AI-generated responses for accuracy, relevance, and alignment with real-world drilling workflows.
• Review content using hands-on familiarity with industry tools and energy data systems.
• Write clear feedback and make careful judgments about technical quality and usefulness.
• Work independently and asynchronously with AI research teams during active projects.

What it pays and takes

This is a fully remote, flexible, project-based contractor role. Prior AI experience is not required.

• Pay: Up to $85 per hour.
• Work arrangement: Part-time contract work with a requirement of 20 or more hours per week.
• Location: Open to candidates in the United States.
• Language: Fluent written English.
• Experience: At least two years of professional experience in drilling, completions, or related energy operations.
• Relevant background: Drilling Engineer, Completions Engineer, Well Cost Analyst, Drilling Superintendent, or an equivalent energy role.
• Tools: Hands-on experience with one or more of WellView, SAP, ComboCurve, and AVEVA PI.
• Skills: Strong written communication, attention to detail, and the ability to work independently in an asynchronous setting.

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 systems that generate and assess text, images, audio, code, and other content. Experienced professionals help by creating examples, reviewing model responses, and explaining what is accurate and useful, which is why specialized industry knowledge matters.],

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