Gen Ai Annotator

Description:

We are looking for detail orientated candidates for the new role of Gen AI Annotator. The ideal candidate has previous experience in effectively coping with a fast-paced, high-pressure role in a constantly changing business environment. They will be client orientated, enthusiastic, courteous, assertive, and motivated to take charge of the development and improvement of AI LLM (large language model).

The candidate must possess a strong aptitude for working with data and excellent verbal and written communication skills. They will be flexible and analytical with the ability to understand and interpret large datasets and applying predefine guidelines, ensuring the accuracy and quality of annotations.

The Gen AI Annotators will be working within and promoting the Company Values – Be Brave, Be Wise, Be Proud and Exceed.

Duties and Responsibilities

Leverage your ability with English comprehension and domain knowledge in the rapidly growing field of Generative AI LLM and join our community of Annotators who play a crucial role in improving LLM.

As an Annotator, your role will be to create, assess, and refine pairs of questions and answers to improve a large language model. You'll generate realistic questions that someone might ask the LLM in a real-life context and provide the best possible answer.

This task will involve you reviewing a set of guidelines, create sample prompts and response in your area of expertise.

• Annotate English data accurately and consistently, and in accordance with predefined annotation guideline

• Evaluate the quality of existing data resources, as well as the output of machine learning classifiers and internal tools

• Develop, implement, and maintain guidelines and procedures for consistent, high-quality classification and content creation and organization

• Perform basic research as needed to annotate accurately

• Provide feedback on the annotation tasks and contribute to the continuous improvement of the data annotation process

• Provide insights regarding observed patterns in the annotated data

• Research new entity categories and best practices for organizing them