Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked.
Canonical Graders Labeling Project
Job description
About the Role
We are looking for detail-oriented and proficient English Data Annotators to support an AI and Generative AI project by reviewing, labeling, and evaluating English-language content to improve machine learning and large language model (LLM) performance.
Project Overview
We are seeking detail-oriented evaluators to assess the quality of AI-generated text outputs across multiple content types, including summaries, writing suggestions, document statistics, and generated content. The project focuses on evaluating outputs using a standardized rubric covering coherence, fluency, conciseness, and depth.
Evaluators will review paired input/output texts and assign quality scores based on predefined criteria. The work requires strong reading comprehension, critical thinking, and excellent written communication skills to provide accurate ratings and constructive feedback.
Key Responsibilities
- Review input and output text pairs across various task categories:
- Evaluate outputs using a scoring rubric for:
- Provide clear written justifications for scores of 4 or below.
- Identify issues related to organization, grammar, redundancy, clarity, and informational quality.
- Ensure evaluations follow project guidelines and quality standards.
- Maintain consistency and objectivity across assigned samples.
- Collaborate with quality assurance reviewers when calibration feedback is provided.
You will be redirected to the company's website to complete your application.