Plant Performance Engineer

What You'll Do7

• Review AI-generated responses about plant performance, reliability, and energy asset management for technical accuracy and relevance.
• Create training examples that reflect real operations workflows and the data you see in tools such as AVEVA PI, WinCC, or Power BI.
• Explain how you diagnose performance issues, manage assets, or interpret SCADA and production data so AI teams understand the domain.
• Score model output against engineering best practices and source material from your professional work.
• Flag errors, missing context, or unsafe assumptions in AI answers and suggest corrections.
• Document your feedback in written form for AI research teams across asynchronous channels.
• Apply hands-on knowledge of at least one listed tool to ground your evaluations in real operational data.

Requirements6

• Two or more years of professional work in industrial operations, plant performance, or energy asset management.
• Background in a role such as Plant Performance Engineer, Reliability Engineer, SCADA Engineer, Drilling or Production Engineer, or Generation Asset Analyst.
• Hands-on use of at least one tool: AVEVA PI, WinCC, Oracle MDM, Power BI, or Bloomberg Terminal.
• Clear written communication and close attention to detail when reviewing technical material.
• Ability to set your own schedule and work without direct supervision in an async setup.
• No prior AI experience needed.

Who Should Apply

The ideal candidate has spent at least two years in plant performance, reliability, SCADA, drilling, production, or generation asset analysis and can point to real use of AVEVA PI, WinCC, Oracle MDM, Power BI, or Bloomberg Terminal. You write with precision, notice when an AI answer misses operational context, and can work on your own schedule without waiting for a team. The role suits people who want part-time, project-based work alongside another job or consulting practice. The role is less suitable if you need a permanent full-time position with a fixed weekly schedule or if you lack direct energy industry experience. Applicants often get rejected when they cannot show the two-year minimum or when their tool experience stays vague; a weak writing sample or a pattern of missing technical details in feedback also lowers fit.

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