How we use AutoML, Multi-task learning and Multi-tower models for Pinterest Ads

People come to Pinterest in an exploration mindset, often engaging with ads the same way they do with organic Pins. Within ads our mission is to help Pinners go from inspiration to action by introducing them to the compelling products and services that…

Building a real-time user action counting system for ads

The Pinterest ads team’s mission is to provide the best experience for both Pinners and advertisers. Our ads system is a real-time bidding system that delivers targeted ads based on a variety of attributes. One…

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…

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 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…

Pin it to Win it: Our First Virtual Pinternship

When our University Recruitment team started planning for the 2020 Pinterns to arrive, our goal was to welcome them to Pinterest and provide them with a memorable experience. As the pandemic quickly changed everyone’s plans, this core goal remained the same and we adapted our strategy to accommodate the…

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…

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…

Building a more inclusive way to search

Every day, tens of millions of people search for ideas on Pinterest, whether it’s a recipe to cook for dinner that night or a new hairstyle to try over the weekend. According to a Pinterest study, 70 percent of people use Pinterest to…

Building the Pinterest app for Windows 10

Solving a user problem As we focus on developing ways to help Pinners find inspiration across all interests, locations and platforms, we knew we had to improve the experience for Windows. Accessing Pinterest from desktop requires using a browser, often times with numerous tabs…

How Pinterest Supercharged its Growth Team With Experiment Idea Review

Growth teams need to be organized bottom-up to scale well The Pinterest Growth team has over 100 members, and we’ve run thousands of experiments over the years. It’s difficult to run that many experiments and still maintain a high success rate over time. We’ve found the traditional growth team model of team leads…

Growth engineering meetup

Synopsis of the talks Paid growth @ Airbnb Ganesh Venkataraman discusses the various channels and techniques…

Optimizing Kafka for the cloud

Takeaways Developing locality aware systems and balancing algorithms can help substantially reduce cost Making Kafka Producer and Consumer rack aware helps efficiently route traffic Data-driven engineering decision making is critical to continuously improve systems One of the fundamental principles when operating in the…

Trusting Metrics at Pinterest

Pinterest, like many tech companies, relies heavily on data to help inform decisions and power machine learning. This strategy fundamentally depends on the data being accurate. Over the years we’ve worked to improve the processes behind trusting core decision-making data and ensure metrics remain accurate. How Data Can Go Wrong …

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!

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…

Upgrading Pinterest operational metrics

Recently, Pinterest hit a major milestone: 300 million monthly active users around the world. To reliably serve this user base with our large content corpus, Pinterest’s engineering team maintains thousands of services all working together in tight…

Setting Up Snowflake Secondary Roles with Tableau

At Pinterest, we heavily utilize Tableau for our enterprise analytics. In an effort to secure access of sensitive data to the appropriate business units, we moved the enterprise data into a Snowflake data warehouse. Using Snowflake as a data platform, we can create and manage…

Automating Shop The Look on Pinterest

Every day, people come to Pinterest to discover new ideas — and when they find a product they want to buy, it should be easy to purchase it. In home decor specifically, millions of people come to Pinterest to find inspiration. That’s why in 2017…

Fighting spam with Guardian, a real-time analytics and rules engine

As the Trust & Safety team, one of our major responsibilities is protecting Pinners from spam. Without protections, spam could potentially be all over Pinterest since spammers can script and generate activity at a rate much higher than actual users. One of…

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…

Automated cluster management and recovery for Rocksplicator

Rocksplicator at Pinterest Rocksplicator (github) was open sourced by Pinterest one and half years ago. It was designed to solve common problems of building large-scale online stateful data systems on commodity hardware, such as RocksDB replication and request routing. Technical details about how Rocksplicator solves…

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.

Building board archiving and sorting

Connor Montgomery | Software engineer, Product Engineering A Pinterest tradition we’ve had since our early days is the Make-a-thon, our twist on a hackathon. Make-a-thons bring together employees from different disciplines to build something new. In the past, we’ve had projects range from scaling hacks to AR prototypes to…

Understanding the product cycle of discovery to purchase on Pinterest

Pinners have always used Pinterest for shopping, as they often come in a planning mindset and are exploring products and…