PinSage: A new graph convolutional neural network for web-scale recommender systems

Deep learning methods have achieved unprecedented performance on a broad range of machine learning and artificial intelligence tasks like visual recognition, speech recognition and machine translation. However, despite amazing progress, deep learning research has mainly focused on data defined on Euclidean domains, such…

Building a dynamic and responsive Pinterest

In 2015, the majority of content on Pinterest was pregenerated for users prior to login. It was stored statically in HBase and served directly upon entering the service. (More details can be found in the blog post Building a smarter home feed.) …

Driving Shopping Upsells from Pinterest Search

Pinterest’s mission is to bring everyone the inspiration to create a life they love. Shopping is at the core of Pinterest’s mission by helping Pinners find and purchase the products they like. Oftentimes when Pinners want to buy…

Using PID controllers to diversify content types on home feed

Every day millions of Pinners visit the home feed to find inspiration on Pinterest. As a member of the home feed ranking team, it’s my job to not only figure out what relevant pins to show Pinners but also to make sure that…

How Pinterest Fights Spam Using Machine Learning

Hundreds of millions of people regularly visit Pinterest to visually discover inspiring ideas among billions of Pins. Inspiration is a high bar and we must be vigilant in ensuring that Pinners don’t see spam, harmful content or misinformation. To enforce our…

Virtual onboarding in the time of COVID-19: The new hire’s new normal

Cindy Xinyi Zhang | Data Scientist, Experimentation and Metrics Science On March 2nd, exactly one week before my full-time position at Pinterest started…

Open sourcing Querybook, Pinterest’s collaborative big data hub

Charlie Gu | Tech Lead, Analytics Platform, Lena Ryoo | Software Engineer, Analytics Platform, and Justin Mejorada-Pier | Engineering Manager, Analytics Platform With more than 300 billion Pins, Pinterest is powering an ever-growing and unique dataset that maps interests, ideas…

Building a universal search system for Pinterest

On Pinterest, the best answer goes beyond text, but can even go beyond an image too. When you’re looking for eye makeup ideas for example, a video personalized to your skin tone range teaching you how to create a certain look is likely…

Developing fast & reliable iOS builds at Pinterest (Part one)

At Pinterest we’re focused on helping people discover inspiring ideas, from dinner recipes to try, home and style products to buy, to places to travel. Building the best products for mobile is a critical part of that, with 80% of all Pinners…

Building a Kubernetes platform at Pinterest

Why Kubernetes? Over the years, 300 million Pinners have saved more than 200 billion Pins on Pinterest across more than 4 billion boards. To serve this vast user base and content pool…

Building interactive email with AMP

AMP (Accelerated Mobile Pages) is an open source technology created by Google to support fast mobile web pages. Over the years, we’ve partnered with Google and adopted AMP technology in our mobile web pages to deliver a faster, more efficient user experience. Most…

Faster Creator Content Distribution at Pinterest

At Pinterest, we are committed to building the best experience for creators to reach and inspire new audiences and for Pinners to easily discover the best ideas for them. We believe more diverse Pin formats and an efficient distribution system that builds a…

Pinterest + ktlint = ❤

Ha pasado casi un año desde que la base de código Android de Pinterest se convirtió en la prioridad de Kotlin, y aproximadamente dos años desde que adoptamos ktlint para el formato y lint de Kotlin. Hoy, compartimos que Pinterest se…

How to Review Code as a Junior Developer

“Just ask questions.” That was the piece of advice that completely changed my perspective on code reviews. I first started as a Software Engineer at Pinterest on the Shopping Partner Experience team right out of college. I focused on my personal learning by reading documentation…

Building a Label-Based Enforcement Pipeline for Trust & Safety

As Pinterest grows with increasing numbers of users and businesses, providing a safe and trustworthy experience is one of our top priorities. Every day the platform serves billions of Pins and boards to inspire Pinners. With so many Pins and activity, It can…

The Fantastic Fixathon

Engineers at Pinterest are always focused on doing what’s best for the product, but working in a codebase that’s clean, well-maintained, and relatively bug-free transforms engineering tasks from being “just work” to enjoyable opportunities to flex our skills. We’re also enriched as engineers, both technically and otherwise, when we take…

User state-based notification volume optimization

Notifications play an important role in helping Pinterest’s 335M+ monthly active users discover and engage with inspiring content. It’s crucial to send the right number of notifications with high quality content. If we send too few notifications, Pinners might miss out on great opportunities…

Refactoring Thrift schemas at Pinterest

The Pinterest tech stack consists of hundreds of microservices written in a variety of languages that use Apache Thrift to communicate with each other. Thrift schemas are used to define our service interfaces, constants and serialized data across all levels of the stack…

Multi-task Learning and Calibration for Utility-based Home Feed Ranking

Home feed is one of the most important surfaces at Pinterest that drives a significant portion of engagement from the more than 400+ million people who visit each month. From a…

Improving HBase backup efficiency at Pinterest

Pinterest has one of the largest HBase production deployments in the industry. HBase is one of the foundational building blocks of our infrastructure and powers many of our critical services including our graph database (Zen), our general-purpose key-value store (UMS), our…

El fantástico Fixathon

Los ingenieros de Pinterest siempre están enfocados en hacer lo mejor para el producto, pero trabajar en una base de código limpia, con buen mantenimiento y relativamente libre de errores transforma las tareas de ingeniería de ser “solo trabajo” a oportunidades agradables para…

Supporting React Native at Pinterest

Early last year, a small group of engineers started investigating the possibility of adopting React Native at Pinterest. We’ve been following the ecosystem with interest since it was first open-sourced in 2015. Since then, a robust community has developed around it, and it’s been…

How Pinterest runs Kafka at scale

Pinterest runs one of the largest Kafka deployments in the cloud. We use Apache Kafka extensively as a message bus to transport data and to power real-time streaming services, ultimately helping more than 250 million Pinners around the world discover and do what…

Detecting Image Similarity in (Near) Real-time Using Apache Flink

Pinterest is a visual platform at its core, so the need to understand and act on images is paramount. A couple of years ago, the Content Quality team designed and implemented our own batch pipeline to detect…

Detecting image similarity using Spark, LSH and TensorFlow

As a visual platform, the ability to learn from images to understand our content is important. In order to detect near-duplicate images we use the NearDup system, a Spark- and TensorFlow-based pipeline. At the core of the pipeline is a Spark implementation of batch…