AI Content Expert II
@ Amazon

Boston, MA
$63,000
On Site
Full Time
Posted 3 hours ago

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XXXXXXXXX XXXXXXXXXXXXX XXXXXXXXXX****** @amazon.com
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Job Details

Job Overview

Amazon is seeking an AI Content Expert II to generate complex annotations, produce high-quality training data, and perform data analysis to enhance AGI's LLM capabilities. This role involves working closely with scientists and engineers to review guidelines, audit work, and identify tool improvements.

Key Responsibilities

  • Create and annotate complex training data in text, image, and video formats.
  • Write grammatically correct texts in various creative styles per provided guidelines.
  • Perform quality audits and reviews on data tasks completed by peers.
  • Make informed decisions in ambiguous situations and implement solutions independently.
  • Identify, report, and suggest tooling improvements and bug fixes.

Basic Qualifications

High-school diploma or equivalent with 2+ years experience in writing, annotation, and data markup. Excellent English proficiency (C2 level) with strong comprehension, research, and attention to detail.

Preferred Qualifications

Bachelor’s degree or equivalent experience. Experience with LLM training data, command line interfaces, basic UNIX commands, scripting (Python), markup languages (HTML, XML, Markdown), and regular expressions.

Key Skills/Competency

  • Annotation
  • Content Generation
  • Data Analysis
  • Training Data
  • Quality Auditing
  • Guidelines
  • UNIX
  • Python
  • Markup Languages
  • LLM
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How to Get Hired at Amazon

🎯 Tips for Getting Hired

  • Research Amazon's culture: Study their mission, values, and recent news.
  • Customize your resume: Highlight annotation and data skills.
  • Showcase technical acumen: Emphasize UNIX and Python knowledge.
  • Prepare for behavioral interviews: Provide examples of quality audits and decisions.

📝 Interview Preparation Advice

Technical Preparation

Review basics of LLM technology.
Practice UNIX shell commands and scripting.
Study Python for data processing.
Familiarize with markup formats like HTML.

Behavioral Questions

Explain handling ambiguous data challenges.
Describe a time you ensured quality accuracy.
Share experiences working in fast-paced settings.
Discuss a collaboration with technical teams.

Frequently Asked Questions