Data Annotator | Architectural Project

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NieokreśloneFull-time
#449198·Dodano 3 dni temu·0
Źródło: Label Your Data
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Tech Stack / Keywords

bounding boxespolygonsRoboflowdata annotationsegmentationAIarchitecturecivil engineering

Firma i stanowisko

Label Your Data is a global data annotation company supporting AI teams with high-quality, secure, and scalable annotation services for Computer Vision and NLP. They have a strong and diverse team of annotation specialists across Europe, LATAM, and Africa, maintaining a 98%+ annotation accuracy benchmark across more than 20 industries, including Automotive, Robotics, Healthcare, E-commerce, Agriculture, Retail, and Fintech. The company supports 55+ languages and is fully GDPR, HIPAA, and CCPA-compliant, with ISO/IEC 27001:2013 and PCI/DSS certifications ensuring high standards of data security and confidentiality. They operate with team hubs in North America, the EU, and Asia and offer services including image and video annotation, text annotation, audio annotation, sensor data annotation, data classification and categorization, data entry and collection, and model validation and QA.

Wymagania

  • Practical understanding of building drawings (plans, facades, sections) or willingness to learn
  • Previous experience in data annotation or performing segmentation tasks
  • Knowledge of annotation techniques using bounding boxes and polygons
  • Attention to detail
  • English language skills to understand instructions and guidelines

Nice to have:

  • Education in architecture, civil engineering, or related fields

Obowiązki

  • Annotate structural elements (walls, windows, doors, columns) and furniture on building plans using bounding boxes
  • Annotate architectural elements (walls, windows, rooms, open spaces, and other zones) using polygons
  • Follow detailed annotation instructions and maintain consistent quality across tasks
  • Use the Roboflow online annotation platform for all tasks

Benefity

  • Full-time work during business hours on weekdays
  • Fully remote work
  • Management support without excessive bureaucracy
  • Compensation in US dollars
  • Opportunities for long-term professional development
Label Your Data

Label Your Data

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