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.

About the team and the role:

Our Recommendations team works on delivering recommendations at scale and in near real time to our buyers on our website and native app platforms. Recommendations are a core part of how our buyers navigate eBay’s vast and varied inventory. Our team develops state-of-the-art recommendations systems, including deep learning based retrieval systems for personalized recommendations, machine learned ranking models, GenAI/LLM powered recommendations, as well as advanced MLOps in a high volume traffic industrial e-commerce setting.

We are building cutting edge recommender systems powered by the latest ML, NLP, LLM/GenAI/RAG and AI technologies. Additionally, we are building production integrations with Google GCP Vertex AI platforms to supercharge our item recommendation algorithms. Come join our innovative engineering and applied research team!

What you will accomplish: Influence how people will interact with eBay’s recommender systems in the future, and how recommender systems technology will evolveWork with unique and large data sets of unstructured multimodal data representing eBay's vast and varied inventory, including billions of items and millions of usersDevelop and deploy state-of-the-art AI models to production which have direct measurable impact on eBay buyersDeploy big data technology and large scale data pipelinesDrive marketplace GMB as well as advertising revenue via organic and sponsored recommendationsWhat you will bring:MS in Computer Science or related area with 6 years of relevant work experience (or BS/BA with 8 years) in Engineering / Machine Learning / AIExperience building large scale distributed applications and expertise in any OO language (Scala, Java, etc.)Experience building with no sql databases and key value stores (MongoDB, Redis, etc)Generalist with a can do attitude and willingness to learn/pick up new skill sets as neededExperience with using cloud services is a plus (GCP is a double plus)Experience with big data pipelines (Hadoop, Spark), AI applied research, industrial recommendation systems, Large Language Models (LLMs) and prompt engineering is a plusLinks to some of our previous work:Google Cloud Blog 2024eBay Tech Blog 2023RecSys 2022 Workshop papereBay Tech Blog 2022RecSys 2021 paper

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eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at talent@ebay.com. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities.

Jobs posted with location as "Remote - United States (Excludes: HI, NM)" excludes residents of Hawaii and New Mexico.

 

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