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' (LLMs) capabilities. This is a fixed term contractual role for 12 months.
Responsibilities

Creating and annotating high-quality complex training data in multiple modalities (text, image, video) on various topics, including technical or science-related content
Writing grammatically correct texts in different styles with various degrees of creativity, strictly adhering to provided guidelines
Performing audits and quality checks of tasks completed by other specialists, if required
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

A day in the life
We are looking for a ML Data Associate (MLDA) to undertake the task of foundational labeling functions, such as dialogue evaluation on speech, text, audio, video data.
Your ability to concentrate, multi-task and your high attention to detail helps you deliver high-quality work as well as maintaining strict confidentiality and follow all applicable Amazon policies for securing confidential information. You will be a part of a diverse team with the shared vision of improving customers’ lives with practical, useful generative AI innovations. An inner drive, individuality, and a creative mind are extremely beneficial.
Basic Qualifications

Bachelor’s degree in a relevant field or equivalent professional experience
2+ years of experience working with written language data, including experience with annotation, and other forms of data markup
Strong understanding of U.S.-based culture, society, and norms
Strong research skills to gather relevant information, understand complex topics, and synthesize multiple resources; understanding of basic academic integrity, i.e. plagiarism
Excellent attention to details and ability to focus for a long period of time
Comfortable with high-school level STEM
Ability to effectively write and evaluate diverse subject matter across various domains
Ability to adapt writing style to suit various style guidelines and customers
Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy

Preferred Qualifications

Strong proficiency in English. Candidate must demonstrate excellent writing, reading, and comprehension skills (C1 level in the Common European Framework CEFR scale)
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
Comfort in annotation work that may include sensitive content

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