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…

Knit Con through an employee’s eyes

Originally published on Tobi’s personal blog. It’s not every day I get to spend two days with my coworkers making arepas, practicing Tai chi, learning how to plate dishes, and vibing to six different DJs. Two days immersing myself in the deepest caverns of…

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…

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…

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…

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…

PinText: A Multitask Text Embedding System in Pinterest

Word embeddings have been actively studied and developed by researchers and practitioners in the machine learning community since the neural network language model was proposed. Researchers not only proposed principled algorithms and open-source code, but they also released pre-trained embedding models with public…

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…

Launching your career as an apprentice engineer at Pinterest

In 2018, after more than a decade focused on environmental sustainability, I decided to start a new career as a software engineer. I enrolled in an immersive software development course in NYC, and a year later I was headed to a software engineering apprenticeship…

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…

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…

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…

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…

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…

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…

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…

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…

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.

Ad Metrics Quality and Testing on Mobile

Every day at Pinterest, we help our advertising partners reach Pinners through different ad formats, and we provide them with metrics and analytics on how their ads are performing. Maintaining our partners’ trust and delivering value is critical, so the metrics we expose…

HierTCN: Deep learning models for dynamic recommendations and inferring user interests

As we build a visual discovery engine, it’s crucial to understand user intent and serve relevant content through recommender systems that constantly learn from a cross-section of data to dynamically predict the next idea a Pinner will love. However, we found…

The Dead Code Society

On June 1, 2018, engineer Chris Lloyd created the #dead-code-society Slack channel to be “a sombre place for remembering [---]-only diffs.” Messages are prefixed by a :tombstone: and include links to diffs that contain only file or line deletions. The channel averages a little over one message per day, but they frequently come in bursts as part of refactoring projects and clean-up efforts. As Pinterest has grown as a company, our software unpinning has grown with it. We have hundreds of software engineers producing thousands of changes per week. The net result is an upward trend in total lines of code with a significant portion of our software having been (re)written in just the last few years. The #dead-code-society has helped balance that trend by celebrating the retirement of code from active service. Retired code remains in source control history to be remembered and consulted, but it no longer occupies a prominent place in our workspaces, build systems, or cognitive periphery. Less is more. Carpe diem.

Seven best practices for inclusive product design

At Pinterest, our mission is to help you discover and do what you love. We’re building a product for everyone, because the best Pinterest is inclusive and easily usable for people with all levels of abilities. That’s why today we’re sharing our…

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 …

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…

How we designed our Continuous Integration System to be more than 50% Faster

Earlier this year, the Engineering Productivity team at Pinterest published a blog called How a one line change decreased our clone times by 99%. In that post, we described how a simple Git configuration sped up clone times in one of our…