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Project Chiron - Assamese Data Trainer at Welo Global
, , India -
Full Time

Start Date

Immediate

Expiry Date

18 Oct, 26

Salary

18.0

Posted On

20 Jul, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Assamese Proficiency, English Proficiency, Data Annotation, Data Labeling, Quality Review, Attention To Detail, Visual Analysis

Industry

Translation and Localization

Description
About the Role We are looking for detail-oriented Trainers to support an AI data annotation project. In this role, you will review pre-seeded questions paired with images and provide accurate "golden" answers based on what you observe in the image. This is a task-based, remote-friendly opportunity ideal for individuals who are meticulous, and able to follow detailed instructions consistently. What You'll Do Review a pre-seeded question along with an accompanying image (e.g., "What is the title of the Excel file based on what you see in the image?") Carefully examine image content to identify the relevant details needed to answer the question Provide a clear, accurate "golden” answer based solely on the visual information provided Flag any images that are unclear, corrupted, or insufficient to answer the question Maintain consistency and quality across a batch of tasks Follow project-specific guidelines and rubrics as provided by the project team What We're Looking For Native/Strong proficiency at Assamese Fluent English proficiency (reading/writing) Bachelor's degree required Strong attention to detail and accuracy Ability to follow written instructions precisely and consistently Reliable access to a computer and internet connection Prior experience with data annotation, data labeling, or quality review is a plus Work Format & Compensation Work Type: freelance, remote Hours/Schedule: 10 hours per week Compensation: $18/hr Duration: Long-term \n \n
Responsibilities
Review pre-seeded questions and images to provide accurate golden answers based on visual information. Flag corrupted or insufficient images and maintain quality consistency across task batches.