7 beste Stellen als applied scientist, amazon robotics in berlin, be – aktuell auf Personalsuche

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Sr. Applied Scientist, Community Data & Science

Amazon Development Center Germany GmbH -
Berlin

Jetzt bewerben

Details zur Stelle

Vollzeit
vor 14 Stunden

Qualifikationen

Doktorat
Informatik
Forschungserfahrung
Master
Machine Learning
Computerlinguistik

Vollständige Stellenbeschreibung

DESCRIPTION

Join Amazon's Community Feedback organization and help transform how billions of customers make purchase decisions. As an Applied Scientist on our team, you'll build intelligent systems that understand, curate, and surface insights from billions of ratings and reviews. You'll drive innovation in multimodal ML, NLP, and agentic AI systems that power core Amazon experiences like review highlights, product insights, and Rufus, directly influencing unregretted purchase decisions for customers worldwide.

Work with one of Amazon's largest and most diverse customer feedback corpora, applying advanced ML to real-world problems at unprecedented scale
Collaborate with a senior, high-performing science team split between Berlin and Barcelona, with opportunities to mentor and grow
Shape the future of customer trust through research in corpus understanding, content quality, and intelligent surfacing systems
Partner with teams across Amazon (Search, Rufus, Personalization) to multiply your impact across the shopping journey

Key job responsibilities

Design, develop, and deploy machine learning models for corpus understanding, including entity extraction, multimodal content analysis (text, images, videos), and structured insight generation at billion-scale
Build and optimize ML systems for content quality assessment, moderation, ranking, and personalized surfacing that directly impact customer experience
Drive end-to-end ownership of scientific initiatives from research and experimentation through production deployment and measurement
Collaborate with product and engineering teams to translate complex ML solutions into scalable, reliable customer experiences
Mentor junior scientists and engineers, providing technical guidance and fostering scientific excellence across the team

A day in the life
The Community Data & Science team focuses on understanding, shaping, structuring, presenting and vending Community Feedback to help customers use the wisdom of the community to make unregretted purchase decisions. We build and own ML solutions that help with i) shaping the community content corpus both in terms of quantity and quality, ii) converting the content into structured data and iii) presenting raw content and structured data to shoppers to inform unregretted purchase decisions. Today, our ML models support experiences like review solicitation and submission, content moderation, rating aggregation, review ranking and review summarization.

BASIC QUALIFICATIONS

PhD in Computer Science, Machine Learning, Statistics, or related quantitative field, or Master's degree with 5+ years of applied research experience
3+ years of experience building and deploying machine learning models in production environments

PREFERRED QUALIFICATIONS

5+ years of experience developing and deploying ML systems at scale, processing billions of data points

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

m/w/d

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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