Drilling/Production Engineer - Energy AI (Remote)
Listing checked September 18, 2026 · pay as published by Handshake AI
Overview
Handshake AI hires energy professionals for project-based work that improves how AI systems handle industrial operations and performance engineering questions. You bring your experience with tools like AVEVA PI, WinCC, or Power BI to judge AI-generated answers and build expert training data. The schedule stays remote and async, with most contributors logging 5 to 20 hours per week during an active project. No prior AI work is needed, and you can take on the fellowship alongside your current role.
What You'll Do8
- 1Review AI responses about drilling, production, and plant performance for accuracy and relevance.
- 2Create reference answers that reflect how an experienced engineer would approach a real operational problem.
- 3Score AI output against accepted practices in energy asset management and industrial operations.
- 4Document your reasoning in clear written notes so research teams can follow your judgment.
- 5Identify missing context, factual errors, or unsafe guidance in AI-generated content.
- 6Annotate workflows, performance metrics, and tool outputs from your own professional experience.
- 7Compare AI suggestions with hands-on knowledge of SCADA, reliability, or generation asset analysis.
- 8Complete project tasks on your own schedule while meeting agreed quality standards.
Requirements8
- 1At least 2 years of professional experience in industrial operations, plant performance, or energy asset management.
- 2A background as a Plant Performance Engineer, Reliability Engineer, SCADA Engineer, Drilling/Production Engineer, Generation Asset Analyst, or similar energy role.
- 3Hands-on use of at least one tool from this list: AVEVA PI, WinCC, Oracle MDM, Power BI, or Bloomberg Terminal.
- 4Strong written communication skills for explaining technical decisions.
- 5Attention to detail when checking AI output for errors and omissions.
- 6Ability to work on your own with AI research teams in an async setting.
- 7No prior AI experience required.
- 8Comfort with project-based work and variable weekly hours.
Who Should Apply
The strongest match has at least two years in industrial operations, plant performance, or energy asset management and can point to hands-on work with AVEVA PI, WinCC, or a similar system. You should enjoy writing clear technical explanations and judging AI answers against real field practice. This role fits engineers who want flexible project work next to a full-time job or other commitments. Less suitable for candidates who need a permanent position, fixed weekly hours, or direct management duties. Applications often fall short when they list energy experience without naming the specific tools used, or when writing samples stay vague about operational data and performance metrics.
Salary Insight
Pay reaches $85 per hour at the top of the range. For project-based AI training in energy and industrial domains, that rate sits near the upper end and often matches contributors with several years of hands-on operations or asset management experience. Expect the final rate to depend on the specific project and your background.
Pay and demand for Machine Learning & AI roles
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$75/hour
This role
up to $85/hr
Most Machine Learning & AI roles pay $54–$100 per hour. This role's pay falls inside that range.
Based on 548 similar roles that publish pay · 95 publish only a top rate; those count at the rate they gave
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Compensation
Up to $85/hr
Required Skills
Application Tip
Name the exact tools you use, such as AVEVA PI, WinCC, or Power BI, and tie each one to a concrete task you handled. Add a short writing sample or bullet that shows how you review operational data, for example a performance issue you diagnosed and the metric that changed. Quantify your experience where you can, like the number of assets you monitored or the size of a production dataset.
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