Tech Blog

A new feature generates customer delight by using modern computer vision techniques to drive new search paradigms through visual discovery.

Several eBay teams worked together to create a plug-in that makes it easy to include accessibility in a design right from the start.

It’s been effective at speeding up productivity, pushed to eBay, and contributed back to the open source community.

A new risk data hub for decisioning can significantly boost variable time-to-market, with high performance under billions of query traffic.

Contract testing has grown in popularity in recent years with the widespread adoption of microservice architectures. In this article, we will share our experiences with contract testing at eBay.

Using the power of natural language understanding, these two students created fantastic solutions.

By leveraging deep learning techniques to compare the titles of product listings, we greatly improved the relevance of our recommended items on eBay’s View Item page.

eBay’s notification platform team built a fault-tolerant, resilient system by injecting faults in the application level.

eBay makes a crucial pivot to OpenTelemetry to better align with industry standards for Observability.

How the powerful meta-analysis method called "weighted z-test" can help eBay become more efficient.

Sellers in the U.S., U.K., Germany, Australia, France, Italy and Spain now have access to Buyer Groups, a new tool which allows them to segment their buyers to drive more repeat business.

Determining which promoted auction items to display in a merchandising placement is a multi-sided customer challenge that presents opportunities to both surface amazing auction inventory to buyers and help sellers boost visibility on their auction listings.

Billions of queries require new, smarter alerting features.

A case study demonstrates how eBay's Notification Engineering team optimizes a streaming system in a microservice architecture to support high-throughput broadcast notifications.

Buyers reveal a whole range of behaviors and interests when they browse our pages, so we decided to incorporate these additional purchase intent signals into our machine learning model to improve the relevance of our recommended items.

The new open feature flagging standard enables companies to deliver cloud-native applications more effectively.

For our annual ML competition, we challenged university students to predict how many days a carrier takes to deliver packages.

Under the new machine learning model, buyers are recommended items that are more aligned to their shopping interests on eBay.

A step-by-step guide on how to build a state-of-the-art recommender system in an industrial setting.

A look at how our eBay technologists created an automatic testing solution for batch applications.