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Thai E-commerce data Annotater

Taiyuan Zhihe Xing Education Technology Co., Ltd

THB 11,000.00 - 15,000.00 / month

monthly

Application ends:

Job Overview

  • Date Posted
    July 14, 2025
  • Location
  • Offered Salary
    THB 11,000.00 - 15,000.00 / month
  • Expiration date
    October 14, 2025
  • Type
  • Industry
    Intelligent Equipment
  • Additional Compensation
    Other
  • Employee Benefits
  • Job Location
    Remote

Summary

Position: E-commerce data Annotater

Job Description

Job responsibilities: Clean up and annotate product data on e-commerce platforms.
Working hours: 5 days a week, 8 hours a day
Job requirements: Fluent in English, Thai native speaker
Work cycle: approximately 3 months
Work from home

Qualifications & Skills

Requirements
Skills and Competencies: Proficient in English and basic computer skills are essential.
Working Conditions: Office environment with potential for remote work.
Qualities and Traits: Detail-oriented, analytical thinker, and strong communicator.
Work experience: Experience in fast-moving consumer goods and e-commerce is preferred
Work platform:Lazada

Company Descriptions

Our business scope is extensive, covering all types of data annotation such as images, speech, text, and videos. In terms of image annotation, we can achieve high-precision object detection, semantic segmentation, key point annotation, etc., providing crucial data support for industries like autonomous driving, intelligent security, and smart home. For speech annotation services, we accurately annotate information such as speech content and emotional tendencies for application scenarios like speech recognition, synthesis, and sentiment analysis. Text annotation can complete tasks such as entity recognition, relationship extraction, and sentiment classification, facilitating the application of natural language processing technology in intelligent customer service, information retrieval, content review, and other fields. Video annotation focuses on target tracking, action recognition, scene classification, etc., laying a solid foundation for video analysis and understanding.