Maintenance Planner - AI Training Project
Listing checked September 18, 2026 · pay as published by Handshake AI
Overview
Handshake AI seeks energy industry professionals for part-time, remote project work that improves how AI systems handle maintenance and reliability tasks. You will use your background in asset management or grid operations to review AI-generated responses and flag gaps in accuracy or relevance. The project calls on hands-on familiarity with tools such as IBM Maximo, Oracle OMS, AVEVA PI, or ArcGIS. Hours stay flexible and asynchronous, with most contributors logging about 5 to 20 hours each week during an active project. No background in AI is needed, and you can fit the work around other commitments.
What You'll Do8
- 1Review AI-generated answers about maintenance planning, asset management, and grid operations for factual errors.
- 2Score each response for relevance to real reliability engineering workflows.
- 3Create expert training examples that reflect your daily work with energy industry tools.
- 4Write concise feedback that explains why an AI response misses key maintenance or outage coordination steps.
- 5Apply hands-on knowledge of IBM Maximo, Oracle OMS, AVEVA PI, or ArcGIS to judge technical accuracy.
- 6Track your completed evaluations and submit them through the project platform.
- 7Coordinate with AI research teams through written messages on an asynchronous schedule.
- 8Flag gaps in reliability engineering logic or distribution operations practices.
Requirements7
- 1At least 2 years of professional experience in asset management, maintenance reliability, or grid operations.
- 2Background as a Maintenance Planner, Reliability Engineer, Outage Coordinator, Distribution Ops Analyst, or a similar energy industry role.
- 3Hands-on use of at least one platform: IBM Maximo, Oracle OMS, AVEVA PI, or ArcGIS.
- 4Clear writing that can explain technical judgments to a research team.
- 5Close attention to detail when checking AI output for errors.
- 6Ability to work on your own and in asynchronous settings with AI research teams.
- 7No prior AI experience needed.
Who Should Apply
The ideal candidate has at least two years in asset management, maintenance reliability, or grid operations and can point to daily use of IBM Maximo, Oracle OMS, AVEVA PI, or ArcGIS. You should enjoy writing short, precise evaluations that separate a correct maintenance workflow from a flawed one. This role fits people who want part-time, remote project work without a fixed schedule. Candidates who lack direct energy industry experience or have never used the listed platforms often score low on fit. Another common reason for rejection is vague written feedback that fails to show how your domain knowledge applies to the AI response.
Salary Insight
The role pays up to $85.00 per hour. That rate reflects specialized energy industry knowledge, so it sits above typical pay for general data annotation or entry-level AI training tasks. Expect project length and hours each week to vary, since most contributors work about 5 to 20 hours during an active project.
Pay and demand for Machine Learning & AI roles
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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 513 similar roles that publish pay · 90 publish only a top rate; those count at the rate they gave
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Most requested skills · share of roles
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Compensation
Up to $85/hr
Required Skills
Application Tip
When you apply, name the exact platforms you have used, such as IBM Maximo, Oracle OMS, AVEVA PI, or ArcGIS, and tie each one to a real task you completed. Add a short writing sample or a bullet that shows how you reviewed a maintenance plan or outage schedule. This gives reviewers proof of both domain depth and the written analysis the project needs.
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