Join OpenTrain as an Engineering Document Review Expert to evaluate technical reports, design documents, and project analyses for AI training — remote contractor role, 20+ hours/week, paid $20–$40 USD/hour. Ideal for engineers with technical-reporting experience.
Generative AI & RLHF
100% Remote Hourly · $20–$40/hr
$20–$40/hr
Compensation
Worldwide
Eligibility
Entry
Experience
Jul 3, 2026
Posted
Open worldwide
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OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help people start and grow freelance careers teaching AI by consolidating opportunities, building a unified portfolio, and making specialized AI training work easy to track and apply for.
OpenTrain AI is the hiring organization for this role. You will work directly with our project teams to shape high-quality training data that helps modern AI systems understand engineering content.
Why AI training matters
AI training (data labeling / annotation) is the human side of building AI: people prepare, evaluate, and improve the examples models learn from. This work is remote, flexible, and a fast-growing way to apply real-world expertise to shape how cutting-edge systems behave.
As an engineering reviewer you’ll contribute domain knowledge that helps models understand technical writing, evaluate engineering reasoning, and generate accurate, practical engineering outputs.
The role
We are recruiting an Engineering Document Review Expert to examine engineering documentation (technical reports, design documents, project analyses), provide written expert feedback, and create real-world examples and problem sets used to train AI. This is a contractor, part-time role requiring 20+ hours per week and remote work.
Tasks combine evaluative rating and text-generation work: you will assess accuracy, clarity, and completeness, produce targeted written clarifications, and contribute best-practice guidance to improve annotations and training examples.
What you’ll do
Review engineering documentation, including technical reports, design documents, and analyses for correctness and clarity.
Provide detailed written feedback and technical clarifications on complex engineering scenarios.
Evaluate submissions using structured rating criteria for accuracy, completeness, and clarity.
Develop real-world engineering examples and problem sets tailored for AI training contexts.
Contribute practical industry best practices, QA suggestions, and methodological improvements.
Requirements
You must have an engineering degree (BSc, MSc, or PhD) in a discipline such as mechanical, civil, electrical, or chemical engineering and experience producing technical reports, design documentation, or in-depth project analyses.
Strong written and verbal communication is required: you must be able to express technical ideas clearly to both technical and non-technical audiences. Comfort working in English with English-language materials is required.
Degree in an engineering discipline (BSc, MSc, or PhD).
Experience creating or reviewing technical reports, design docs, or project analyses.
Clear, precise written communication and ability to explain complex engineering concepts.
Familiarity with industry standards, regulatory compliance, or QA processes is a plus.
Who should apply
This role is suited to practicing or recently practicing engineers, consulting engineers, technical leads, or academics who regularly produce or review engineering documentation and want flexible, remote contract work.
Entry-level applicants with the required degree and demonstrable technical-reporting experience are welcome; the role asks for domain-accurate reviews and clear written feedback rather than long professional tenure.
How it works — schedule, pay, and next steps
This is a contract, part-time position requiring 20+ hours per week and is open worldwide. Tasks are document-based and delivered remotely through OpenTrain AI’s workflows.
Pay is hourly in USD: $20–$40 per hour (hourlyRate: $40 listed). Labeling work includes evaluation ratings and text-generation contributions against document data.
To apply, prepare examples of technical reports or documentation you’ve written or reviewed and be ready to demonstrate clear written feedback on sample engineering content.
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