Architecture Content Reviewer
Listed on 2026-08-02
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Science
AI Evaluation, Data Annotation/ AI Labeling
About Open Train
Open Train is the #1 platform for people building careers in AI training and data labeling. We help contributors discover projects, build a unified AI-training portfolio, and grow a durable freelance career focused on the human side of AI.
As the hiring organization for this role, Open Train offers accessible, cutting-edge work that is fully remote and flexible — ideal for licensed professionals who want part-time, impactful work shaping how AI understands real-world domains.
About AI training work in architectureAI training (also called data labeling or human feedback) is the human expertise behind how models learn. In architecture-focused projects you’ll teach models to reason about building design, codes, workflows, and tools by reviewing outputs, answering domain questions, and providing structured feedback.
This work is frequently part-time and remote, and it places experienced practitioners at the center of how AI systems learn to produce accurate, code-compliant, and practice-aware answers.
The roleTitle:
Architecture Content Reviewer — contractor, part-time, remote (United States only).
You will review and evaluate AI-generated written content about architecture, rate answer quality, provide corrections and explanations from professional practice, and recommend references and workflows the model should know.
- Employment type:
Contractor, part-time - Location:
United States (remote) - Language:
Professional working English - Pay: USD $65–$90 per hour (_HOUR)
This role blends evaluation and short text-generation work. Expect to assess AI responses, assign evaluation ratings, and produce concise, evidence-based feedback that improves model outputs.
- Review and evaluate written content and model responses for technical accuracy, code compliance, and practical relevance.
- Provide written corrections, clarifications, and examples grounded in real-world practice.
- Answer domain‑specific questions and explain reasoning clearly for model training.
- Identify and suggest authoritative reference material (codes, standards, manufacturer data) relevant to prompts and responses.
- Share practical insight into architectural workflows, tools, and standards (e.g., Revit, AutoCAD, BIM, IBC).
- Collaborate with a small group of subject‑matter experts to align feedback and tagging conventions.
Candidates must meet the professional and eligibility requirements below. These are firm; we cannot accept applications without a U.S. architecture license.
- Professional architecture license in the United States (required).
- At least 2 years of professional architecture experience across residential, commercial, or institutional projects.
- Familiarity with building codes and standards (for example, IBC) and with tools such as Revit, AutoCAD, BIM, or equivalents.
- Professional working English proficiency and an ability to write clear, structured feedback.
- Based in the United States and able to work as a contractor.
This is a flexible, part-time contractor role. The role description indicates a reliable commitment of about 10 hours per week; the structured time Requirement field lists 20+ hours/week, so candidates should expect a flexible weekly workload (typical engagements target roughly 10 hours/week but may increase during project phases).
Pay is hourly and ranges from $65 to $90 per hour. Work involves text-based review and rating tasks (dataType: TEXT; label types: , ).
- Compensation:
Hourly, USD $65–$90/hr. - Typical tools: everyday AI assistants for drafting and reviewing; you will use standard office software and may need to access shared annotation tools.
- Time commitment: target ~10 hours/week (see note above about potential variability).
This role is ideal for licensed architects who want to apply their practice knowledge to shape how AI understands design, codes, and workflows. You do not need prior annotation experience, but you should be comfortable giving clear, concise written feedback.
Helpful but not required: a portfolio of built or realized work (not purely conceptual), and familiarity with consumer AI tools (e.g., ChatGPT or similar).
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