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…

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 …

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…

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…

How We Protect Pinners’ Passwords

Aalaa Satti | Software Engineer Amine Kamel | Head of Production Security At Pinterest, one method by which we ensure account security is through protecting Pinners’ passwords. Passwords can be problematic for a variety of reasons, including the fact that people tend to reuse their…

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…

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…

The evolution of search at Pinterest

When Pinterest first launched it provided a new way for people to collect and organize ideas from around the web. What started as a place to save though, quickly became a unique service for discovery where Pinners could draw inspiration from each other, brands and…

Understanding product attributes for shoppers

Every day, people come to Pinterest to shop and find ideas in categories like home and fashion, and it’s our responsibility to show them the most relevant and inspiring products. We measure relevance in a few different dimensions, but most importantly…

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 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…

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…

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…

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…

Improving the Quality of Recommended Pins with Lightweight Ranking

The Pinterest corpus is composed of billions of Pins, however, each Pinner only sees a small subset based on their interests when…

How we increased engagement using automatic personalized copy testing

Think about the last time you visited a website. Was there a word that helped draw you in? Now think about how that might be different if you spoke a different language, were a different age or grew up in a different part of…

Growth engineering meetup

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

One year in at Pinterest and looking ahead as we grow

A little over a year ago, I joined Pinterest as the SVP of Technology. The world looks different than I thought it would around my first “Pinniversary”, but the opportunities before us are more apparent and abundant than ever before. For me personally, I’m…

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…

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…

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…

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…

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…

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. …