Applied Researcher Intern (PhD)
2026 Applied Researcher Intern (Ph.D.)
If you are interested in being considered for this role, then please apply via our RippleMatch link:
https://app.ripplematch.com/t/8bc6c4c9
At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.
Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.
Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.
***Please submit only ONE application for eBay. Duplicate applications from the same candidate will result in all applications for that candidate being automatically declined. ***
***Note: By applying to this position, your application will be considered for multiple teams based in our locations in:
- San Jose, CA
- New York, NY
- Austin, TX
About the role:
Applied Researcher - Intern (PhD)
Looking to help shape the future of global commerce? Grow as an Applied Researcher? Work on interesting projects with business impact?
Build machine learning models (NLP/NLU/CV/etc.)to deliver insightful yet practical solutions as part of building online products across our various groups.
Leverage advanced AI technologies, such as Large Language Models (LLMs) and Multimodal LLMs, to create solutions that simplify and enhance customer interactions on eBay’s platform.
Apply Research and Engineering methodologies to solve real world, production level problems. Work with engineers as well as other cross functional teams to produce end-to-end production-ready solutions.
Conduct experiments and evaluate the performance of algorithms, investigate false positives/false negatives and implement continuous improvements to the eBay ecosystem.
Identify opportunities to implement Machine learning and AI into various areas of our Global Marketplace.
What you will accomplish:
You will be directly responsible for conceiving and building machine learning solutions.
Design and implement end to end solutions using machine learning, and own live deployments to improve both efficiency and user experience for buyers and sellers across our Marketplace.
Collaborate with other researchers, engineers, and product teams to develop strategic and tactical enhancements to our platforms.
Conduct experiments and evaluate the performance of the models, investigate false positives/false negatives and implement continuous improvements to the eBay ecosystem
Research, assess, recommend, and develop technologies in the context of eBay’s Marketplace product requirements. Contribute to eBay’s patent portfolio.
Communicate your methodology and results to a community of researchers, developers, analysts, and product managers working on a number of related technologies.
Work with engineers as well as other cross functional teams to produce end-to-end production-ready solutions.
What you will bring:
Currently enrolled as a US student, 0-3 years of relevant work experience in an accredited PhD program within the United States graduating after December 2026 or Summer 2027.
Enrolled in or pursuing a PhD Degree or Masters degree in Data Science, Computer Science, Statistics or related major.
Creative thinker with an interest in building real-world products.
Practical experience with Engineering/Programming/Coding. Strong mathematical, statistical, and scientific modeling skills
Hands-on Technical experience (Academic experience is ok) with some of the following technologies: Python, Pytorch, Docker. Familiarity with: Hadoop
The pay range for this position at commencement of employment in California, Washington, or New York City is expected in the range below.
$4,080- $5,520 Bi-weekly (Every two weeks).
Pay offered may vary depending on multiple individualized factors, including Location, Education level, Skills, and Experience.