Architecture & Design QA Lead - Remote
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About the Role
**Job Description** **Job Title:** Architecture & Design Quality Assurance Lead **Job Type:** Contract **Location:** Remote **About This Role** In this hourly, remote contractor role, you will work as an Architecture&Design Quality Assurance Lead to oversee quality, consistency, and trainer performance across architecture, interior design, urban design, and built-environment AI training projects. You will review AI-generated architecture/design content
Key Skills for This Role
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About This Role
- In this hourly, remote contractor role, you will work as an Architecture&Design Quality Assurance Lead to oversee quality, consistency, and trainer performance across architecture, interior design, urban design, and built-environment AI training projects.
- You will review AI-generated architecture/design content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards.
- You will assess work for design accuracy, spatial reasoning, architectural terminology, building-systems awareness, code/safety sensitivity, sustainability considerations, visual/design logic, clarity, formatting, instruction-following, and adherence to project-specific rubrics.
- You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently.
- This role requires strong architecture/design expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote expert teams.
- This role is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs.
- Your architecture/design quality leadership will directly help improve the world’s premier AI models by ensuring that architecture and design training data is accurate, context-aware, visually coherent, practical, well-explained, and aligned with client expectations.
- Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.
- Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise.
- This will also provide you with access to future projects available through our expert network.
- Your profile
- Bachelor’s, Master’s, or professional degree in Architecture, Interior Design, Urban Design, Landscape Architecture, Environmental Design, Industrial Design, Planning, or a closely related field.
- Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.
- 3+ years of experience in architecture, design, interiors, urban design, design research, construction documentation, teaching, design review, visualization, or related built-environment workflows.
- Strong understanding of design principles, spatial organization, circulation, scale, proportion, materiality, accessibility, sustainability, building systems, construction logic, and design communication.
- Ability to evaluate architecture/design content against detailed rubrics and identify issues such as impractical layouts, poor spatial reasoning, code-insensitive suggestions, weak design rationale, accessibility gaps, unsafe assumptions, or unrealistic construction recommendations.
- Familiarity with tools or methods such as AutoCAD, Revit, Rhino, SketchUp, Adobe Creative Suite, BIM, construction drawings, precedent analysis, site analysis, rendering, or design presentations is preferred.
- Experience leading or supporting remote teams of designers, reviewers, annotators, educators, visual QA specialists, or domain experts is strongly preferred.
- Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
- Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
- Experience with AI training, data annotation, LLM evaluation, design QA, visual review, architectural review, or rubric-based review is a strong plus.
Key Responsibilities
- Quality monitoring: Spot-check architecture/design items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
- Design review: Evaluate AI-generated architecture/design explanations, spatial layouts, design concepts, material recommendations, building-system descriptions, accessibility considerations, and design reasoning for accuracy and practicality.
- Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and architecture/design-specific review standards.
- Question handling: Respond to trainer/QA questions clearly and promptly, especially around spatial logic, design terminology, accessibility, sustainability, construction feasibility, materials, and rubric interpretation.
- Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
- Documentation: Create and maintain architecture/design project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
- Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and architecture/design-specific review requirements.
- Quality alignment: Ensure all trainers and QAs apply architecture/design review guidelines consistently and understand updates as projects evolve.
- Risk review: Flag unsafe, inaccessible, impractical, misleading, code-insensitive, or poorly contextualized architecture/design recommendations.
- Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for architecture/design AI training projects.
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