Amazon

DESCRIPTION

Amazon is looking for an AI Content Expert II - German 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.

Key job responsibilities

As an AI Content Expert, you will be responsible for creating training data in German that are complex in nature and will require you to make informed and high judgement decisions in each case. You will be working closely with scientists and engineers to review and update guidelines, identify tooling improvement opportunities, and engage in conversations regarding the quality of data. Your key responsibilities will include (but not limited to) the below:

• 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

About the team

About AWS

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

Mentorship & Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

BASIC QUALIFICATIONS

• C1+ or equivalent fluency in German language
• High-School or equivalent diploma.
• 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

• 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.
• Comfort in annotation work that may include sensitive content.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $40,400/year in our lowest geographic market up to $86,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.