Label Your Data – Data Annotation & Labeling
Label Your Data – Data Annotation & Labeling
Label Your Data – Data Annotation & Labeling ұйымдарға сапалы оқыту деректерін дайындау арқылы машиналық оқыту және жасанды интеллект жүйелерін құруға көмектеседі. Оның басқарылатын және өз бетінше пайдаланылатын қызметтері кескін, бейне, аудио, мәтін және табиғи тілді өңдеу, 3D нүктелер бұлттары мен LiDAR, медициналық кескіндер, геокеңістіктік деректер және контентті модерациялауды, сондай-ақ деректерді жинау, жасау және енгізу мен үлкен тілдік модельдерді дәл баптауды қолдауды қамтиды. Компания автомобиль өнеркәсібі, денсаулық сақтау, өндіріс, дрондар, робототехника, бөлшек сауда және қаржы сияқты салалардағы машиналық оқыту инженерлерімен, жасанды интеллект топтарымен, өнім менеджерлерімен және зерттеушілермен жұмыс істейді. Бұл ретте икемді жұмыс процестері, нақты бір құралға тәуелсіз интеграциялар және сапаға бағытталған қызмет көрсету келісімдері пайдаланылады.

Remote Architectural Blueprint Data Annotator

Label Your Data is seeking a remote Data Annotator to label architectural blueprints for a construction-documentation AI project. The role uses bounding boxes, polygons, and Roboflow to support spatial engineering model training.

Сипаттама

  • Label structural features such as walls, windows, doors, columns, and furniture on building floor plans with bounding boxes
  • Mark architectural features including walls, rooms, outdoor areas, and other zones with polygon annotations
  • Apply detailed labeling guidelines consistently to maintain quality across assignments
  • Complete annotation tasks using the Roboflow online platform
  • Support AI training by identifying structural elements, spaces, and symbols in architectural blueprints

Талаптар

  • Practical knowledge of construction drawings, including plans, elevations, and sections, or a strong willingness to learn
  • Strong attention to detail
  • English proficiency at B1 level or higher for reading instructions and basic conversation
  • Completed or ongoing degree in architecture, civil engineering, or a related discipline is advantageous
  • Previous experience with data annotation or segmentation tasks is advantageous
  • Familiarity with bounding-box and polygon annotation methods is advantageous

Артықшылықтар

  • Full-time weekday schedule during business hours
  • Fully remote working arrangement
  • Supportive management with minimal bureaucracy
  • Competitive compensation paid in USD
  • Potential for long-term professional development

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