Amazon
$165k-$210kSan Francisco4mo
cursorelevenlabsdecagon
2027 Applied Scientist Internship – PhD, Amazon University Talent Acquisition
AI in this role
Conduct advanced AI research and develop production-ready machine learning and generative AI systems as a PhD intern.
pythonpytorchtensorflow
ragai-agentscomputer-visionnlpmachine-learningdeep-learninggenerative-airesearch
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 power live sports experiences for Prime Video, developing multimodal GenAI solutions for AWS document intelligence, creating agentic AI systems that reason and act autonomously, or advancing recommendation models that transform how customers discover content — depending on the team you're 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.
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 Israel, including but not limited to;
• Prime Video Sports — Build innovative sports experiences for Prime Video, spanning computer vision, 3D simulation, and personalized content recommendations.
• Personalization — Leverage LLMs, NLP, and recommender systems to match customers with products that align with their passions and shopping preferences.
• Agentic AI — Build next-generation agentic AI systems that automate real-world knowledge work, spanning retrieval-augmented generation, multi-agent workflows, long-term memory and personalization, knowledge-graph construction, and agent evaluation.
• DS3 Textract — Develop multimodal generative AI algorithms that pioneer state-of-the-art document understanding solutions impacting millions of customers.
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. Some teams offer full-time internships (3–6 months) while others offer part-time positions (50–60%, 8–12 months) — your recruiter will confirm the format during team matching.
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
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.
How we rate this
2027 Applied Scientist Internship – PhD, Amazon University Talent Acquisition at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Classification
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
RAGAI AgentsComputer VisionNLPMachine LearningDeep LearningGenerative AIResearch
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Tell me about a project where machine learning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: RAG, AI Agents, Computer Vision, NLP, and Machine Learning. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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