2027 Applied Scientist Internship – PhD, Amazon University Talent Acquisition
Amazon is hiring a 2027 Applied Scientist Internship – PhD, Amazon University Talent Acquisition in Bucharest, Romania. Level rates it ; you can apply on Amazon.
Level's read on this job
- Level rates this applied scientist role Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include Python, PyTorch and TensorFlow.
- Level classifies it as an internship.
- Level lists 21,000+ other open roles at Amazon.
- The role was posted in the last few days.
AI in this role
Ph.D. intern role focused on researching, designing, and deploying end-to-end machine learning and AI systems into production at scale.
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 graph-based ML models and knowledge graphs that detect and remediate access violations at global scale, developing behavioral pattern clustering and automated reasoning systems for security operations, or researching multimodal and computer vision approaches on product catalog data to improve safety and compliance mechanisms — 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 generally hire interns for multiple teams in Romania, including but not limited to;
• CoSS — Research and develop ML solutions that improve safety and compliance across Amazon's entire product catalog working with tabular, textual, and product image data using deep learning, computer vision, LLMs, and multimodal models
• Monitored Access Detection — Build AI-driven detection and remediation systems that identify global access violations across Amazon — leveraging knowledge graphs, graph modeling, behavioral pattern clustering, generative AI, and reinforcement learning to create a self-improving, closed-loop security system.
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.
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 both 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.
How we rate this
2027 Applied Scientist Internship – PhD, Amazon University Talent Acquisition at Amazon rates 95 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.
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. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in applied scientist jobs at this level
Pay
- Typical applied scientist job
- $172k
This posting doesn't list pay. Use the typical applied scientist figure when pay comes up. See applied scientist jobs
Questions you could be asked
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where natural language processing was part of your work. What did you do?
- Tell me about a project where algorithm design was part of your work. What did you do?
- Walk me through how you've used Python in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Computer vision, Machine learning, Natural Language Processing, Algorithm Design, and Python. 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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