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…

Partitioning Pinlater for Fun(?) and Profit(!)

Contained within the November 2015 announcement of the open-sourcing of Pinlater, our asynchronous job execution system, was a description of some of the improvements that had been made to the system since the original 2014 blog post describing its creation. Notable among…

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…

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…

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…

How ads indexing works at Pinterest

Introduction Ads indexing is a data processing pipeline that builds servable ad documents for the ads delivering stack at Pinterest, including ads targeting, retrieval, ranking and auction. The pipeline converts ad campaigns in the raw format to the servable format via a heavy computational…

Three-day no-meeting schedule for engineers

About 100 days ago, our product engineering team began experimenting with a three-day no-meeting schedule for individual contributors on our teams. It’s not a big revelation that software development requires long stretches of uninterrupted time to focus. As Pinterest has grown…

Four lessons in making Pinterest faster on Android

As engineers, we intuitively know that a faster app is a better experience for Pinners, but we also have proof that when web pages load faster, user growth improves. Last year, we doubled down on performance across our platforms so…

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…

API Profiling at Pinterest

When I walked into Pinterest on the first day of my internship and learned I’d be focusing on profiling the API Gateway service — the core backend service of the Pinterest product — my only thought was “What is profiling?”. Profiling is often shoved aside…

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…

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…

Improving data processing efficiency using partial deserialization of Thrift

At Pinterest we’ve worked to greatly improve data processing efficiency. One quote that resonates with our unique approach is from writer Antoine de Saint-Exupéry: “Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away.” Ultimately…

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…

Real-time User Signal Serving for Feature Engineering

More than 320 million unique visitors come to Pinterest every month to discover inspiring content, which also gives advertisers a unique opportunity to get their products in front of people with commercial intent. Curation…

People Behind the Product: Meet Rahim Daya, Head of International Product & Toronto Lead

Rahim Daya, Toronto-native and Pinployee of nearly 4 years, leads Pinterest’s International Product as well as the Tech team in Toronto. Ahead of our virtual Pinterest Engineering: Meet the Toronto Team event, get to know Rahim and learn more about…

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 Pin stats

A few months back, we started building a way for businesses to create and showcase their latest and favorite content on their profiles. We also wanted to make it easier for businesses to understand how their Pins are performing. If a business can…

User retention at Pinterest: tackling an ambiguous problem

User retention is an important but nebulous idea. It’s hard to acquire users and even harder to help them feel at home through an engaging and relevant experience. So when some of those users start to leave the platform, your first thought is…

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…

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…

Keeping Related Pins fresh

If you’ve ever heard someone mention “the Pinterest Rabbit Hole,” they’re likely referring to Related Pins, the ideas you see below a Pin you’ve tapped. Related Pins is a feed of content relevant to the closeup Pin and accounts for 40 percent of engagement…

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…

Cómo redujimos el tamaño de la aplicación de Pinterest para iOS en más de un 30% / 50 MB

This blog was originally published in English. To read the English version, click here. Todos sabemos que el tamaño de las aplicaciones es importante (el tamaño de descarga[1] y el tamaño de instalación local[2]). Además, existe una correlación…

Goku: Building a scalable and high performant time series database system

Co-authored by Jinghan Xu, Jian Wang & Tian-Ying Chang, Engineers At Pinterest, developers rely on Statsboard to monitor their systems and discover issues. A reliable and efficient monitoring system is very important for development velocity. Historically, we’ve used OpenTSDB to ingest and…