Mandarin Electrical Engineering QA Review With Document Matching

About OpenTrain AI

OpenTrain AI is the #1 platform for building careers in AI training and data labeling. We connect contributors with hands-on work that teaches and shapes modern AI systems and offer paid contract opportunities to grow skills and experience in this fast-moving field.

• We focus on realistic, paid contracts that let you learn and contribute to how AI behaves.
• OpenTrain contributors work remotely and choose schedules that fit their lives.

About AI training work

AI training (data labeling / annotation / human feedback) is the human work behind reliable AI. Tasks range from writing and rating model responses to matching answers to source documents for retrieval-augmented generation (RAG).

This role supports RAG pipelines: every answer must be fully supported and precisely cited from the documents we provide so models can retrieve correct, auditable evidence.

• Work is remote, flexible, and often suitable for part-time schedules.
• Many projects need domain knowledge rather than prior labeling experience — specialists are in demand and well compensated.

The role

You will review a dataset of 50–100 Mandarin question–answer pairs about electrical engineering, assess each pair using existing feedback, and find supporting documents for each answer using our document-finding tool. Your goal is to ensure every answer is correct, clear, and fully supported by citations from the provided document set.

• Dataset and per-item feedback are provided; you will not create the Q&A from scratch.
• Work supports RAG workflows — every accepted answer must include one or more exact document citations.

What you'll do

This is a detail-oriented, domain-focused review and citation task. Expect to spend ~20 minutes per case on average; total project time is estimated at 20–40 hours depending on speed and accuracy.

• Review 50–100 Mandarin Q&A pairs and the existing feedback for each.
• Use the provided document-finding tool to locate supporting documents from the supplied corpus.
• Verify that each answer is factually correct and add precise citations showing where evidence comes from.
• Mark items as good/bad or needs revision per the provided feedback schema.
• Write brief reviewer notes when an answer is incorrect or unsupported and suggest the correct citation or revision.

Requirements

You must be fluent in Mandarin and able to read technical Chinese sources. The role requires intermediate-level electrical engineering knowledge so you can judge answer correctness and match them to appropriate technical documents.

• Fluent written Mandarin (reading and writing) — required.
• Intermediate background in electrical engineering (education or work) — required.
• Experience using document search or retrieval tools is helpful.
• Reliable internet access and ability to work 20+ hours per week — required.

Preferred qualifications

The following are strong pluses but not strictly required. Include them in your application if they apply.

• Work or internship experience at a large semiconductor company — big bonus.
• Prior annotation or QA experience on technical datasets.
• Familiarity with retrieval-augmented generation (RAG) workflows or citation-first review.

Compensation, schedule, and how it works

This is a contractor, part-time role with pay at USD 40 per hour. The project is estimated at ~20–40 hours total; you should be available for at least 20 hours per week while active on the project.

OpenTrain AI provides the dataset, per-item feedback, and the document corpus plus the document-finding tool. You will submit reviewed items with documented citations and reviewer notes according to the project template we provide.

• Pay type: Hourly contractor at $40 USD/hour.
• Time commitment: ~20–40 total hours; 20+ hours/week expected during engagement.
• Work type: Remote, contract / part-time.
• Label/type: Text review and prompt-response writing (PROMPT_RESPONSE_WRITING_SFT).