About the Role

Amazon is hiring an AI Content Expert II to create and annotate high-quality training data for Large Language Models. The role involves writing and evaluating content in multiple modalities, making judgment calls on ambiguous information, and collaborating with scientists and engineers. This is a fixed-term contract position requiring German language proficiency and strong attention to detail.

Key Responsibilities

• Creating and annotating high-quality complex training data in multiple modalities
• Writing grammatically correct texts in different styles adhering to guidelines
• Performing audits and quality checks of tasks completed by other specialists
• Making sound judgments and logical decisions with ambiguous or incomplete information
• Identifying and reporting tooling bugs and suggesting improvements

Required Skills & Qualifications

Must Have:

• High-School or equivalent diploma
• Proven experience working with written language data, including annotation and data markup
• CEFR C1 or equivalent fluency in German language
• Written and spoken knowledge of English (CEFR C1)
• Strong understanding of U.S.-based culture, society, and norms
• Strong research skills and understanding of basic academic integrity
• Excellent attention to details and ability to focus for long periods
• Comfortable with high-school level STEM
• Ability to effectively write and evaluate diverse subject matter
• Ability to adapt writing style to various guidelines and customers
• Ability to adapt to fast-paced environments with changing circumstances

Nice to Have:

• Bachelor’s degree in a relevant field or equivalent professional experience
• Experience with creating complex data for LLM training and evaluation
• Proven 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