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…

Virtual onboarding in the time of COVID-19: The new hire’s new normal

Cindy Xinyi Zhang | Data Scientist, Experimentation and Metrics Science On March 2nd, exactly one week before my full-time position at Pinterest started…

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 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…

How Pinterest runs Traffic-based Interlinking experiments for SEO

Search Engine Optimization, or SEO, is an important channel for people to find ideas and inspiration on Pinterest, and can also help expose new users to first use cases, such as hairstyle tutorials or a home office setup. …

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…

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…

Driving Shopping Upsells from Pinterest Search

Pinterest’s mission is to bring everyone the inspiration to create a life they love. Shopping is at the core of Pinterest’s mission by helping Pinners find and purchase the products they like. Oftentimes when Pinners want to buy…

Contextual relevance in ads ranking

Pinterest runs an ads marketplace that balances value for Pinners, partners, and the business. We initially used engagement prediction as our main method to balance the marketplace before eventually adding contextual relevance to increase Pinner value. We have three main surfaces for determining…

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…

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…

Using Kafka to throttle QPS on MySQL shards in bulk write APIs

At Pinterest, backend core services are in charge of various operations on pins, boards, and users from both Pinners and internal services. While Pinners’ operations are identified as online traffic because of real-time response, internal traffic is identified as offline because processing is…

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…

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…

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…

PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest

As we build a visual discovery engine that powers 2B+ Pins, it’s crucial to understand user interests and preferences in…

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…

Improving HBase backup efficiency at Pinterest

Pinterest has one of the largest HBase production deployments in the industry. HBase is one of the foundational building blocks of our infrastructure and powers many of our critical services including our graph database (Zen), our general-purpose key-value store (UMS), our…

Detecting Image Similarity in (Near) Real-time Using Apache Flink

Pinterest is a visual platform at its core, so the need to understand and act on images is paramount. A couple of years ago, the Content Quality team designed and implemented our own batch pipeline to detect…

Building interactive email with AMP

AMP (Accelerated Mobile Pages) is an open source technology created by Google to support fast mobile web pages. Over the years, we’ve partnered with Google and adopted AMP technology in our mobile web pages to deliver a faster, more efficient user experience. Most…

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…

Looking inside the technology that powers Pinterest

Pinterest began as a small startup, and has grown to a company that serves +175B Pins to +250M people. While we have one of the largest datasets online, we have 600+ engineers, and so technology needs to be accessible for each person to play their part in…

Interest Taxonomy: A knowledge graph management system for content understanding at Pinterest

Interest Taxonomy at Pinterest We recently began rolling out the beta version of Pinterest Trends, a new tool that gives a view of the top U.S. search terms on Pinterest within the past 12 months, and a look into when search terms peak for…

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…