Amazon
2027 Applied Scientist Internship – PhD, Amazon University Talent Acquisition
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
We're building systems that turn research into real-world impact
We're building systems that turn research into real-world impact — ensuring flawless streaming for millions of Prime Video customers, shaping the future of AI-driven shopping with Rufus, advancing speech generation and conversational AI, optimizing large-scale infrastructure through intelligent observability, and transforming how people and jobs find each other. If this sounds interesting to you then we have a range of opportunities for you to explore.
We're 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 won't 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;
- https://www.amazon.science/
- https://amazon.jobs/content/en/career-programs/university/science
- https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science
Key job responsibilities
As an Applied Science Intern, you will own the design and development of end-to-end systems. You'll 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 Amazon's 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
You'll spend your first weeks scoping your project with your mentor, then own the research and implementation end-to-end.
Your work could involve building computer vision models that detect quality issues across Prime Video's content library, developing multimodal AI solutions that power Amazon's shopping assistant Rufus, creating automated reasoning tools that verify distributed systems at scale, engineering intelligent observability frameworks for large-scale infrastructure, or advancing recommendation models that connect people with the right jobs — depending on the team you're matched with.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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
We're hiring interns for multiple teams in the UK, including but not limited to;
• Prime Video Video Quality Analysis – Develops AI and machine learning solutions using computer vision, audio processing, and generative AI to detect and prevent streaming quality issues across Prime Video's vast content library • Rufus Features Science UK – Shapes AI-driven shopping experiences at Amazon, working on projects from enabling Rufus to take actions on behalf of customers to generating multimodal answers combining text, image, audio, and video. • READI – Observability, Triage & Peak Readiness – Builds intelligent log analytics and automated performance frameworks that transform system telemetry into actionable insights for large-scale distributed systems. • Automated Reasoning Group – Ensures program and systems correctness through deductive proof, model checking, formal verification, and runtime conformance monitoring for large-scale distributed systems.
You'll submit a single application and we'll 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 3–6 months. Please note, each team has different start date and duration preferences — your recruiter will confirm the preferences of the team you're matched with prior to interviewing.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
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.
Basic Qualifications:
- 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
Preferred Qualifications:
- Have publications at top-tier peer-reviewed conferences or journals
- Experience in solving business problems through machine learning, data mining and statistical algorithms
- Experience in designing experiments and statistical analysis of results
- Experience implementing algorithms using toolkits and self-developed code
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.
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.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London