ML Data Associate – German, Frontier AI Data Services

You will contribute to AI model improvement by delivering accurately labeled training data across text, speech, audio, image, and video modalities. Your work directly supports the quality of Amazon's AI products by ensuring training data meets rigorous standards.

Amazon is investing in generative AI and the responsible development and deployment of large language models (LLMs) across all of our businesses. We are looking for candidates who bring fresh perspectives and find new approaches to solve complex challenges.

We value precision, consistency, and the ability to follow detailed guidelines accurately.

Key job responsibilities
- Maintain and follow strict confidentiality as customer privacy is our most important tenet.
- Deliver high-quality labeled data, using guidelines provided to meet KPIs and using in-house tools and software, as part of Amazon's commitment to developing and deploying AI responsibly.
- Work with a range of different types of data including: text, speech, audio, image, and video.
- Work across teams and with subject matter experts to improve workflows and build a better understanding of customer intent for any given dataset.
- Demonstrate proficiency in generating high-quality human insight data across a range of modalities, inclusive of text, image, video, and audio.
- Make sound judgments and logical decisions when faced with ambiguous or incomplete information.
- Strong attention to detail and ability to transition between different task types as priorities shift.
- Support daily operational deliverables for multiple task types assigned to you and the team.
- Flag error patterns and escalate to team managers with documented examples for resolution.
- Report process gaps or Standard Operating Procedures (SOP) issues to your team lead for review.
- Identify day-to-day process and operational issues in SOP and tools and suggest changes to unblock operations.
- Support peers by answering task-related questions during execution when needed.

A day in the life
No two projects look exactly alike, so your day-to-day will vary depending on the workflow you’re assigned to. That said, most days follow a familiar rhythm. Weekly team huddles are held by the Team Managers to elevate priorities, guideline updates, and quality feedback. You log into the labeling platform and work through your assigned task queue — this could be evaluating AI-generated dialogue, annotating images, reviewing video, or rating audio quality, which are repetitive by nature. Typically, you spend 6–8 hours of screen-based work per shift with scheduled breaks. You are expected to meet daily throughput targets while maintaining a quality score at or above the team threshold. Ambiguous or non-standard tasks can be an opportunity to work through the situation independently before discussing your approach with your team lead or designated point of contact, where applicable, to ensure alignment. Your work is regularly audited by QA auditors, and you will receive documented feedback on accuracy. Calibration sessions take place occasionally, typically after a dip in quality, to realign the team on labeling standards. You will have a 1:1 with your manager once a month to discuss performance metrics and development.

This role involves repetitive, guideline-driven labeling tasks for 6–8 hours per shift on screen and working with a range of data types, which may include sensitive or potentially distressing content. Work is queue-based, metric-tracked (quality score and throughput), and regularly audited by QA reviewers. This is not an AI research or model development role. You will not be designing algorithms or making product decisions.


About the team
Knowledge Fulfillment Engine – Frontier AI Data Services provides high-quality labeled data for machine learning technologies that power Amazon's AI products. Your labeled data feeds directly into AI model training, though you may not always see the final product your work enables, the labeled data your team provides is the engine that drives AI Model development growth for Amazon and our customers.

Basic qualifications

- A degree or related work experience
- Advanced proficiency in German language (CEFR C1+)
- Language fluency in both spoken and written English (CEFR C1+)
- Experience in business writing and demonstrated ability to create reports, proposals, and professional correspondence
- Experience in research, gathering and synthesizing information from multiple sources

Preferred qualifications

- Experience using open-source resources for research
- Experience in project coordination or management (for support functions teams)
- Experience managing stakeholder relationships across departments
- Attention to detail in managing tasks and documents, with the ability to adapt to evolving guidelines and specifications
- Analytical thinking and structured problem-solving capabilities
- Proficiency in Microsoft Office Suite and common business applications.

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.

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