Reliability Engineer - Remote Energy AI Project

What You'll Do7

• Create expert training examples from your everyday work in plant performance, reliability, or asset management.
• Review AI-generated answers and judge their accuracy against real energy operations practices.
• Flag technical mistakes, missing context, or unsafe recommendations in model outputs.
• Write feedback that explains correct workflows, calculations, or equipment behavior to AI researchers.
• Use tools such as AVEVA PI, WinCC, Oracle MDM, Power BI, or Bloomberg Terminal to validate examples.
• Coordinate with research teams through async messages and shared project notes.
• Log project hours and track progress across active assignments.

Requirements7

• At least 2 years of professional experience in industrial operations, plant performance, or energy asset management.
• Background in a role such as Reliability Engineer, Plant Performance Engineer, SCADA Engineer, Drilling or Production Engineer, or Generation Asset Analyst.
• Hands-on use of at least one tool from this list: AVEVA PI, WinCC, Oracle MDM, Power BI, or Bloomberg Terminal.
• Strong written communication skills, with the ability to explain technical topics in plain language.
• Sharp attention to detail when checking numbers, assumptions, and operational logic.
• Comfort working on your own schedule and managing your own project time.
• No prior AI experience required.

Who Should Apply

The role fits energy professionals with at least two years in plant performance, reliability, industrial operations, or asset management. You may come from a SCADA, drilling, production, or generation asset analysis background, and you use tools like AVEVA PI, WinCC, or Power BI on the job. This work is less suitable for someone who wants a fixed full-time schedule, steady project length, or hands-on plant shifts. Applicants often score low when they list energy experience in broad terms but cannot show specific tools, assets, or operational decisions. Another common miss is weak writing samples that do not explain technical ideas in plain language.

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