Building Expanded Targeting for Pinterest Ads

With more than 300 million people coming to Pinterest each month, Pinterest offers unique opportunities for advertisers to get their products in front of people with commercial intent. Similar to other platforms, Pinterest offers a variety of advertising targeting products¹. Advertisers can…

Adventures in big data wonderland: Going down the Pinterest Path

Have you ever started looking for plants on Pinterest, only to end up shopping for pillows instead? Ever find yourself layers of Pins deep into finding a new idea, not sure of how you got there or where you started? When Pinners are in…

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…

The top Pinterest Engineering blog posts of 2018

The most-read posts of the year Three-day no-meeting schedule for engineers A one year PWA retrospective Supporting React Native How Pinterest runs Kafka at scale How switching our domain structure unlocked international growth PinSage: A new graph convolutional neural network for web-scale recommender systems Looking inside the technology that powers Pinterest Building a more inclusive way to search Building a real-time user action counting system for ads Goku: Building a scalable and high performant time series database system We’ll be back in 2019 with more updates from the team. Happy New Year!

Bottoms-Up: How the Pinterest growth team decentralizes team structure

On the growth team at Pinterest, we describe our structure as “bottoms-up”, meaning ideas and responsibilities flow throughout the team in a way that provides a lot of autonomy to work on the projects each person wants to tackle, across a variety of roles. The…

Empowering Pinterest data scientists and machine learning engineers with PySpark

Data scientists and machine learning engineers at Pinterest found themselves hitting major challenges with existing tools. Hive and Presto were readily accessible tools for large scale data transformations, but complex logic…

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…

Simplifying web deploys

Over the past six months, Pinterest has moved to a CI/CD model for our API and web layers, which has truly improved agility by reducing time between merge and production. Prior to…

Using graph algorithms to optimize Kafka operations, Part 1

Pinterest uses Kafka across the board for data movement. The Logging Platform team alone manages over 3,000 Kafka brokers transporting trillions of messages per day to help bring more than 320 million monthly active Pinners the inspiration to create a life they love. …

Geo-blocking media content on Pinterest

Pinterest engineers are tasked with showing Pinners the best ideas related to their interests, which includes taking into account signals like location. As part of these efforts, we built a video and image platform to enable a…

Calidad y pruebas de las métricas publicitarias en dispositivos móviles

En Pinterest, todos los días ayudamos a nuestros socios de publicidad a llegar a los usuarios a través de diferentes formatos de anuncios y les ofrecemos métricas y análisis sobre el rendimiento de sus anuncios. Mantener la confianza…

An update on Pixie, Pinterest’s recommendation system

We recently welcomed engineers to our offices for our annual Mad Science Fair, where I shared the latest on Pixie, an advanced graph-based recommendation system. Here’s a recap of that talk, and you can find the video here. As Pinterest grows to more…

Hybrid Search: Building a textual and visual discovery experience at Pinterest

As a visual discovery engine, Pinterest helps you discover ideas even when you don’t know what you’re looking for, or have the words to describe it. Using a mix of technology (including visual search) and community input (thanks to the 175B+ Pins…

A one year PWA retrospective

The idea of building a “Progressive Web App” (PWA) is not new, but its definition has changed with the emergence of key technologies like service workers. Now it’s finally possible to build great experiences in a mobile browser. Being an early adopter can…

Introducing Pinqueue3.0, Pinterest’s next-gen content moderation platform

In 2016, we reached a milestone of launching Pinqueue2.0, which has since become the go-to content moderation tool for the engineering, community, and data science teams. One of our top priorities at Pinterest is fostering a safe and trustworthy experience for all…

Pinterest + ktlint = ❤

It’s been nearly a year since Pinterest’s Android codebase became Kotlin-first, and about two years since we adopted ktlint for Kotlin linting and formatting. Today, we’re sharing that Pinterest has officially taken ownership over the project. Initially, we chose ktlint because of its…

La evolución de la búsqueda en Pinterest

This blog article was originally posted in English. To read the English version click here. Cuando Pinterest se lanzó por primera vez, ofrecía una nueva forma de recopilar y organizar ideas de toda la web. Sin embargo, lo que comenzó como un lugar…

Privacy Power-Up: Upgrading Pin Links from HTTP to HTTPS

HTTPS should be everywhere. Your website likely runs over HTTPS, giving your users a secure, encrypted connection, but what about all the outbound links? Can you guarantee that they all use HTTPS? In this post, we describe the steps we took…

Introducing inclusive beauty searches for mobile

This week, we’re announcing skin tone ranges is coming to iOS (followed by Android) so Pinners can discover relevant hair and makeup ideas. Over the coming weeks, when Pinners search for beauty ideas on their iPhone or iPad app, a palette representing a range of skin tones will appear. The palette enables them to personalized Pins and videos they see. By combining the latest in machine learning and inclusive product development, we’re able to directly respond to Pinner feedback and build a more useful product. Last year, nearly 60% of the top 100 search terms for skin-related searches involved a tone, such as dark skin, pale skin, and olive skin, which showed us women of all skin types wanted a way to customize their searches. Keep an eye out for a deeper look at the design process behind the product. Acknowledgements: Emma Herold, Lulu Cheng, Long Cheng, Yixue Li, Larkin Brown, Candice Morgan, Xixia Wang, and Laksh Bhasin.

How we built rearranging Pins

Listening to user feedback is essential to building a product Pinners love and use to discover and save ideas every day. Often, their feature requests present interesting technical challenges for our engineers. For example, today we launched the ability to…

Pin2Interest: A scalable system for content classification

Content understanding is at the core of any great recommendation system. By knowing what each Pin is about, Pinterest can connect Pinners with the most relevant and inspiring content that best matches their interests. Taxonomy of interests The Interest Taxonomy captures popular concepts that appear within Pinterest…

What it’s like to interview at Pinterest

Interviews have traditionally been thought of as an unpleasant but necessary experience. Candidates often find them stressful and many come in having had poor interview experiences in the past. However, interviews are the clearest opportunity for companies to articulate and demonstrate…

Powering inclusive search & recommendations with our new visual skin tone model

To truly bring everyone the inspiration to create a life they love, Pinterest is committed to content diversity and to developing inclusive search and recommendation engines…

Managing Videos on Android

Video launched on the Pinterest Android app in 2016 with the goal of bringing a seamless video experience to the app. This included the ability to support multiple videos per screen, while dynamically controlling their playback state by automatically pausing them when they’ve scrolled…

Pinterest Flink Deployment Framework

Background At Pinterest, stream processing allows us to unlock value from real time data for pinners and partners. The Stream Processing Platform team is working on building a reliable and scalable platform to support many critical streaming applications including real-time experiment analytics…