Mandarin Electrical Engineering QA Reviewer
About OpenTrain
OpenTrain AI is the hiring and contracting organization for this role. OpenTrain is the #1 platform for finding and building careers in AI training and data labeling, connecting contributors with projects that help shape how modern AI systems work.
- Free account creation and application through OpenTrain
- Remote contract work with flexible scheduling
- Opportunity to contribute to cutting-edge AI development
About AI Training and Retrieval-Augmented Generation
AI training is the human side of building artificial intelligence. People review examples, evaluate model responses, and prepare reliable training data so AI systems can produce more accurate and useful results.
This project focuses on retrieval-augmented generation, or RAG. RAG systems use documents to support their answers, so careful review is essential to confirm that each response is fully supported and properly cited by the available source material.
- Help improve the quality and reliability of AI-generated answers
- Work with question-and-answer data and supporting documents
- Use subject-matter knowledge to identify accuracy and evidence issues
The Role
OpenTrain AI is looking for an intermediate reviewer to evaluate Mandarin electrical engineering question-and-answer pairs for a RAG project. A dataset of 50-100 pairs is provided, along with feedback indicating whether each response is good or bad.
You will review the existing pairs, locate matching documents using the provided document set and document-finding tool, and determine whether each answer is fully supported and cited by the available sources. Each case is estimated to take approximately 20 minutes.
- Role: Mandarin electrical engineering question-and-answer pair reviewer
- Estimated workload: 20-40 hours total, depending on performance and speed
- Time requirement: 20 or more hours per week
- Pay: $40 USD per hour
- Engagement: Part-time contractor
What You'll Do
Your work will focus on checking the relationship between questions, answers, feedback, and source documents. The goal is to help ensure that answers in the dataset are accurate, relevant, and completely supported by the documents available for retrieval.
- Review 50-100 Mandarin electrical engineering question-and-answer pairs
- Use existing feedback to understand whether responses have been assessed as good or bad
- Find matching documents with the provided document set and document-finding tool
- Check whether each answer is fully supported by the available documents
- Verify that answers include appropriate citations to supporting material
- Complete each case in approximately 20 minutes when possible
Requirements
This is an intermediate-level project suited to someone with practical or academic familiarity with electrical engineering. The role involves reviewing technical answers and judging whether document evidence adequately supports them.
- Intermediate experience level
- Background in electrical engineering through education or employment is ideal
- Experience at a large semiconductor company is a significant bonus
- Availability to work 20 or more hours per week
- Ability to review Mandarin electrical engineering question-and-answer content
- Careful attention to evidence, answer quality, and citations
Why This Work Matters
Every major AI system depends on people who prepare, evaluate, and improve its training data. By reviewing technical answers against source documents, you will help make AI systems more dependable for specialized electrical engineering questions.
AI training work can be a flexible way to contribute to technology from anywhere. Contributors use their language ability, professional experience, and subject expertise to influence how rapidly evolving AI systems behave.
- Contribute directly to the quality of specialized AI outputs
- Apply electrical engineering expertise to an advanced RAG evaluation project
- Work remotely with a flexible part-time contractor schedule
How to Apply
Create a free OpenTrain account and apply through OpenTrain AI. Include relevant electrical engineering education or employment experience, and highlight any background with a large semiconductor company.
- Review the project details and submit your application
- Showcase relevant electrical engineering experience
- Indicate your availability for 20 or more hours per week