Label Your Data – Data Annotation & Labeling
Label Your Data – Data Annotation & Labeling
Label Your Data – Data Annotation & Labeling tashkilotlarga yuqori sifatli o‘quv ma’lumotlarini tayyorlash orqali mashinaviy o‘rganish va sun’iy intellekt tizimlarini yaratishda yordam beradi. Kompaniyaning boshqariladigan va mustaqil foydalanish uchun mo‘ljallangan xizmatlari tasvir, video, audio, matn va tabiiy tilni qayta ishlash, 3D nuqtalar bulutlari va LiDAR, tibbiy tasvirlar, geofazoviy ma’lumotlar hamda kontent moderatsiyasini, shuningdek ma’lumotlarni yig‘ish, yaratish, kiritish va katta til modellarini nozik sozlash bo‘yicha yordamni qamrab oladi. Kompaniya avtomobilsozlik, sog‘liqni saqlash, ishlab chiqarish, dronlar, robototexnika, chakana savdo va moliya kabi sohalardagi mashinaviy o‘rganish muhandislari, sun’iy intellekt jamoalari, mahsulot menejerlari va tadqiqotchilar bilan ishlaydi. Bunda moslashuvchan ish jarayonlari, muayyan vositaga bog‘liq bo‘lmagan integratsiyalar va sifatga yo‘naltirilgan xizmat kelishuvlaridan foydalaniladi.

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.

Tavsif

  • 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

Talablar

  • 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

Imtiyozlar

  • 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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