Onyx Annotation (Hebrew) – QA 

Description: 

QA Annotators will review image-based annotation tasks to ensure accuracy, completeness, and compliance with project guidelines. They will focus on quality assurance of text detection, boxing, transcription, and error labeling, as well as identify and report recurring error trends. 

They will:

• Review all text present in images to ensure complete and accurate text boxing, with no missed text elements. 

• Perform QA checks on text boxing, transcription, and flagging, ensuring all annotations meet required standards. 

• Verify that error labels are correctly applied to all relevant boxes, or confirm when no errors are present. 

• Conduct a full image review to ensure overall annotation accuracy and consistency. 

• Submit completed QA tasks promptly after confirming all checks are completed. 

• Identify, track, and document error trends, defined as errors that occur repeatedly during QA reviews. 

• Prepare a QA report, clearly outlining detected issues, error trends, and observations. 

• Adhere to project guidelines, quality benchmarks, and turnaround time requirements. 

Purpose:  

This project will help improve AI-related technologies. 

Main Requirements: 

• Hebrew speaker 

• Strong attention to detail and high accuracy in reviewing annotated data. 

• Ability to identify both individual errors and recurring quality issues. 

• Good written communication skills for documenting QA findings and reports. 

• Familiarity with image annotation, text recognition, or data labeling workflows is an advantage. 

• Ability to work independently and manage multiple QA tasks efficiently.