2027 Applied Scientist Internship – PhD, Amazon University Talent Acquisition

Were building systems that turn research into real-world impact helping hundreds of millions of customers make better purchase decisions through AI-powered content understanding enabling robots to autonomously fulfill customer orders at warehouse scale advancing multilingual ML to expand Amazon features across global markets building LLM-based services that automate complex troubleshooting and optimizing query processing for one of the worlds most widely used cloud data warehouses. If this sounds interesting to you then we have a range of opportunities for you to explore.

Were looking for PhD students across multiple research domains to invent design and implement state-of-the-art solutions for never-before-solved problems. Your work here wont just stay in a notebook it ships to production and reaches customers worldwide.

Check out the details below including the job responsibilities team details and basic qualifications before submitting your application.

You can find more information about the Amazon Science community as well as interview preparation tips via the links below;

- job responsibilities
As an Applied Science Intern you will own the design and development of end-to-end systems. Youll have the opportunity to write technical white papers create roadmaps and drive production level projects that will support Amazon Science.

You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms models or other technical solutions whilst experiencing Amazons customer focused culture.

The ideal intern should have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems.


A day in the life
Youll spend your first weeks scoping your project with your mentor then own the research and implementation end-to-end.

Your work could involve building NLP and multimodal ML systems that help customers make smarter purchase decisions developing computer vision and motion planning for autonomous robotic picking creating LLM-based tools for automated troubleshooting and synthetic data generation advancing multilingual ML models that scale Amazon features across languages or tackling query optimization challenges for distributed database systems at cloud scale depending on the team youre matched with.

Many interns publish at top-tier conferences or see their work deployed to production before the internship ends. Interns may also be considered for a return offer at the end of their internship subject to performance evaluation and headcount availability.

Many interns publish at top-tier conferences or see their work deployed to production before the internship ends. Interns may also be considered for a return offer at the end of their internship subject to performance evaluation and headcount availability.

Further benefits of an Amazon Science internship include;

- All of our internships offer a competitive salary
- Interns are paired with an experienced manager and mentor(s)
- Interns get invited to different intern program or office events
- Interns can build their professional and personal network with other Amazon Scientists
- Interns can potentially publish work at top tier conferences

About the team
Were hiring interns for multiple teams in Germany including but not limited to;

Community Data & Science Build ML systems that understand structure and present customer-generated content (ratings text images and video) to help customers make better purchase decisions spanning content moderation ranking summarization and insight extraction at scale

Vulcan Pick (Robotics) Develop an advanced robotic picking system that autonomously identifies and extracts items from warehouse shelves combining computer vision robotic manipulation ML and motion planning to fulfill customer orders in live warehouse operations at scale.

Content Systems Science & Engineering Develop foundational computer vision and AI for Amazons product catalog from vision-language models and real-time inference to AI-powered content validation visual search and content understanding systems.

Cosmos (INTech) Build models tools and metrics that automate the multilingual expansion of ML solutions powering Amazon features across global stores and languages beyond US/English.

NDGE Science Build LLM-based services for automated troubleshooting including model-based and human-in-the-loop evaluation tool-augmented reasoning and synthetic data generation for evaluating and fine-tuning language models.

DBS Redshift Tackle distributed database challenges at cloud scale working on query optimization system auto-tuning materialized views and query processing for Amazon Redshift one of the most widely used cloud data warehouses.

Youll submit a single application and well match you with science teams best aligned with your research interests.

Applications are reviewed on a rolling basis and your application stays active until we find a team match or confirm there are no matches available.

Start dates are available throughout the year for durations of between 36 months. Please note each team has different start date and duration preferences your recruiter will confirm the preferences of the team youre matched with prior to interviewing.

We offer science internships in multiple locations across the EMEA region and you can indicate your interest in all these locations by applying here (Austria Estonia France Germany Ireland Israel Italy Jordan Luxembourg Netherlands Poland Romania South Africa Spain Sweden UAE and UK).

Please note we do not offer remote internships.

- Are enrolled in a PhD in computer science machine learning engineering or related fields
- Experience programming in Java C Python or related language
- Speak write and read fluently in English

- Have publications at top-tier peer-reviewed conferences or journals
- Experience in designing experiments and statistical analysis of results
- Experience implementing algorithms using toolkits and self-developed code
- Experience in solving business problems through machine learning data mining and statistical algorithms

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 ( to know more about how we collect use and transfer the personal data of our candidates.

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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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

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