Plant Performance Engineer - Remote Contract
Listing checked September 18, 2026 · pay as published by Handshake AI
Overview
Handshake AI hires energy professionals for project-based contract work that improves how AI models handle industrial operations. You bring your own experience with plant performance, energy asset management, or reliability work and use it to judge AI-generated answers for accuracy and relevance. Your daily tools matter here: AVEVA PI, WinCC, Power BI, and similar platforms give you the context to create expert training data and flag gaps. The schedule stays flexible, with most contributors putting in 5 to 20 hours each week and no minimum hour requirement. You can join active projects when needs match your background.
What You'll Do7
- 1Review AI-generated responses about plant performance, reliability, and energy asset management for technical accuracy and relevance.
- 2Create training examples that reflect real operations workflows and the data you see in tools such as AVEVA PI, WinCC, or Power BI.
- 3Explain how you diagnose performance issues, manage assets, or interpret SCADA and production data so AI teams understand the domain.
- 4Score model output against engineering best practices and source material from your professional work.
- 5Flag errors, missing context, or unsafe assumptions in AI answers and suggest corrections.
- 6Document your feedback in written form for AI research teams across asynchronous channels.
- 7Apply hands-on knowledge of at least one listed tool to ground your evaluations in real operational data.
Requirements6
- 1Two or more years of professional work in industrial operations, plant performance, or energy asset management.
- 2Background in a role such as Plant Performance Engineer, Reliability Engineer, SCADA Engineer, Drilling or Production Engineer, or Generation Asset Analyst.
- 3Hands-on use of at least one tool: AVEVA PI, WinCC, Oracle MDM, Power BI, or Bloomberg Terminal.
- 4Clear written communication and close attention to detail when reviewing technical material.
- 5Ability to set your own schedule and work without direct supervision in an async setup.
- 6No 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.
Salary Insight
The listing advertises up to $85.00 per hour for this contract. The figure sits near the top of part-time AI training rates for specialized engineering domains. Your exact pay depends on the project and your background, but the posted ceiling reflects the value Handshake AI places on domain expertise.
Pay and demand for Machine Learning & AI roles
AggregatedTypical pay
$75/hour
This role
up to $85/hr
Most Machine Learning & AI roles pay $55–$100 per hour. This role's pay falls inside that range.
Based on 627 similar roles that publish pay · 103 publish only a top rate; those count at the rate they gave
Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.
- Live similar roles
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- Listed in last 30 days
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Hiring most right now: micro1 (301) · Mercor (105) · Handshake AI (68)
Most requested skills · share of roles
- python16%
- technical writing9%
- llm evaluation7%
- data annotation6%
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Compensation
Up to $85/hr
Required Skills
Application Tip
Lead with your two or more years in plant performance, reliability, or energy asset management, then name the exact tools from the posting that you have used, such as AVEVA PI, WinCC, Oracle MDM, Power BI, or Bloomberg Terminal. Add one short example of a real operations problem you diagnosed with those tools, because the project rewards specific, verifiable domain detail over broad claims.
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