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Architecture Expert

Job Description

The future of AI — whether in training or evaluation, classical ML or agentic workflows — starts with high-quality data.

At HumanSignal, we’re building the platform that powers the creation, curation, and evaluation of that data. From fine-tuning foundation models to validating agent behaviors in production, our tools are used by leading AI teams to ensure models are grounded in real-world signal, not noise.

Our open-source product, Label Studio, has become the de facto standard for labeling and evaluating data across modalities — from text and images to time series and agents-in-environments. With over 250,000 users and hundreds of millions of labeled samples, it’s the most widely adopted OSS solution for teams working on building AI systems.

Label Studio Enterprise builds on that traction with the security, collaboration, and scalability features needed to support mission-critical AI pipelines — powering everything from model training datasets to eval test sets to continuous feedback loops.We started before foundation models were mainstream, and we’re doubling down now that AI is eating the world. If you’re excited to help leading AI teams build smarter, more accurate systems — we’d love to talk.

Architecture Expert

Location: Remote

Type: Part-Time Contract (10-20 hours/week, flexible scheduling)

Duration: 3-6 months with potential for ongoing work

Compensation: Commensurate with experience


About the Project

You’ll annotate architectural floor plans to train computer vision models that automatically recognize and segment building elements - contributing to cutting-edge technology that transforms how spaces are designed and visualized.


What You’ll Do

  • Annotate architectural floor plans using our Label Studio Enterprise platform to identify and segment:

    • Core infrastructure (elevators, stairs, shafts, mechanical rooms)
    • Doors (single, double, swing, emergency exits)
    • Restrooms and accessibility features
    • Structural elements (columns, walls)
    • Service areas (janitor closets, electrical rooms, AHU rooms)
  • Ensure geometric accuracy (closed polygons, continuous walls, proper right angles)

  • Follow strict annotation guidelines to maintain consistency across the dataset

  • Identify rare or missing elements across floor plans

  • Participate in weekly calibration sessions to review edge cases and maintain quality standards

  • Meet quality benchmarks for accuracy, completeness, and consistency


Basic Qualifications

Required Experience

  • Strong proficiency reading architectural floor plans(AutoCAD, Revit, or hand-drawn)
  • Understanding of architectural symbols and conventions
  • Knowledge of building systems and core building elements
  • Familiarity with building codes and accessibility standards(ADA compliance, fire exits, etc.)
  • Exceptional attention to detail and ability to maintain focus on precise work

Skills & Attributes

  • Excellent visual-spatial reasoning
  • Consistency and reliability in work quality
  • Self-motivated with ability to work independently
  • Strong communication skills for flagging issues
  • Comfortable with feedback and iterative improvement
  • Minimum 10 hours per week availability for at least 3 months

Nice-to-Haves

Preferred Background

  • Formal education in architecture or related field (any level)
  • Experience with commercial/corporate office design
  • Familiarity with MEP systems (mechanical, electrical, plumbing)
  • Understanding of structural systems and load-bearing elements

Technical Experience

  • CAD software proficiency(AutoCAD, Revit, ArchiCAD, SketchUp)
  • Experience with vector graphics or image editing tools
  • Prior data annotation or labeling experience
  • Exposure to machine learning or computer vision concepts
  • GIS or spatial data analysis experience

Work Style

  • Pattern recognition skills - quickly identifying repeated elements
  • Systematic, methodical approach to reviewing work
  • Problem-solving mindset for handling ambiguous cases
  • Interest in AI/ML applications in architecture
  • Previous remote work experience

What Makes Someone Successful in This Role

You’re highly detail-oriented- You notice when walls don’t align or when accessibility features are missing. Small inconsistencies don’t escape your attention.

You understand spatial relationships- You can mentally visualize 3D spaces from 2D drawings and understand why buildings are organized the way they are.

You’re consistent- You find satisfaction in doing precise work to a high standard and take pride in quality craftsmanship.

You’re a clear communicator- You flag problems early, ask clarifying questions, and aren’t afraid to say “I’m not sure about this element.”

You’re curious about technology- You’re genuinely interested in how AI learns from annotated data and see value in the intersection of architecture and machine learning.

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