AI Content Expert II, AGI Data Services

AI Content Expert II

Amazon is looking for an AI Content Expert II to help with annotations, content generation, and data analysis. As part of the Data Team, you will be responsible for delivering high-quality training data to improve and expand AGI's Large Language Models' capabilities. Key job responsibilities include creating and annotating high-quality complex training data in multiple modalities (text, image, video) on various topics, including technical or science-related content. You will also be writing grammatically correct texts in different styles with various degrees of creativity, strictly adhering to provided guidelines. Additionally, you will be performing audits and quality checks of tasks completed by other specialists, if required. You will be making sound judgments and logical decisions when faced with ambiguous or incomplete information while performing tasks. Diving deep into issues and implementing solutions independently, identifying and reporting tooling bugs and suggesting improvements.

Basic qualifications include an associate's degree or related work experience, 2+ years of experience working with written language data, including experience with annotation, and other forms of data markup. Strong proficiency in English is required, along with excellent writing, reading, and comprehension skills. Strong understanding of U.S.-based culture, society, and norms is also necessary. Strong research skills to gather relevant information, understand complex topics, and synthesize multiple resources; understanding of basic academic integrity, i.e. plagiarism is required. Excellent attention to details and ability to focus for a long period of time are also needed. Comfortable with high-school level STEM, ability to effectively write and evaluate diverse subject matter across various domains, and ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy are also required.

Preferred qualifications include a bachelor's degree in a relevant field or equivalent professional experience, experience with creating complex data for LLM training and evaluation, 1+ year(s) of experience working with command line interfaces and basic UNIX commands, familiarity with common markup languages such as HTML, XML, Markdown, familiarity with common standard text formats such as JSON, CSV, RTF, working knowledge of Python or another scripting language, familiarity with regular expressions syntax, familiarity with Large Language Models, and comfort in annotation work that may include sensitive content.