Projects
With 300B human-curated ideas, Pinterest is the biggest image-rich data set ever assembled. This lets us do interesting things like analyze trends, understand intent and predict consumer behavior. And we’re just scratching the surface of what’s possible.
Machine learning at Pinterest
Tens of millions of people interact with Pinterest each day, browsing, searching and discovering ideas inspired by their tastes. To help make it all happen, Pinterest’s researchers and engineers build new computer vision models that “see” the content of each Pin, filtering abusive and misleading content, optimize ad placements and rank nearly 300 billion Pins daily
Delivering relevant ads to Pinners
Pinterest is where people go to plan and shop, making ideas and ads from brands helpful in taking Pinners from inspiration to action. It’s our goal to ensure ads continue to be additive and not intrusive on Pinterest...
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Advertiser recommendation systems
The Ads Intelligence team at Pinterest is charged with building and maintaining machine learning and algorithm-driven recommendations and the Recommendations Ranker to provide advertisers with the best experience in reaching relevant Pinners and help them reach their campaign goals...
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How Pinterest fights spam
Hundreds of millions of people visit Pinterest each month to discover ideas among billions of Pins. Inspiration is a high bar and so we must be vigilant in ensuring Pinners don’t see spam, harmful content, or misinformation...
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Multi-task learning for products recommendations
People have always come to Pinterest for shopping inspiration, and we’ve made big strides over the years to make that as seamless as possible...
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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...
Read moreComputer vision
Pinterest is at the forefront of visual discovery and recommendations development. With the launch of Pinterest Lens, people use their camera phone to get recommendations inspired by objects they see in the real world. Our browser extension also gives them recommendations based on images they find on Pinterest, or around the web. So far, we’ve detected over a billion visual objects, and now serve 250M+ visual searches each month. But there are still many challenging problems yet to be solved in fine grained recognition, object-to-object visual search, large-scale visual search infrastructure, and a deeper understanding of mediums like video.
How Pinterest is teaching its computers to see
Picture this: You’re checking out a produce stand at the local farmer’s market and see a weird mango-like thing. It looks appealing. But you have no idea what it is or what to do with it, and the seller is busy with another customer...
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Building Pinterest Lens: a real world visual discovery system
Recently, we announced Lens BETA, a new way to discover objects and ideas from the world around on you using your phone’s camera...
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Introducing automatic object detection to visual search
When we launched visual search last year, we gave a first look at what’s possible when you use images as search queries...
Read moreUser modeling and recommendations
Pinterest is one of the largest-scale recommender systems around, serving users more than 10 billion recommendations every day. By combining the data we’ve amassed over the years with human curation, we’ve built human-centered personalization engines that can serve the right recommendation to the right person at the right moment, choosing from a pool of over 300 billion objects—all in real time.
Machine Learning at Pinterest, MLconf 2017
Pinterest is building the world’s largest catalog of ideas. These ideas are embodied in billions of Pins and well over 100 million Users and Boards which, together, form a complex picture of our users and their interests...
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Applying deep learning to Related Pins
One of the most popular ways people find ideas on Pinterest is through Related Pins, an item-to-item recommendations system that uses collaborative filtering...
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Pinnability: Machine learning in the home feed
Pinterest hosts more than 30 billion Pins (and growing) with rich contextual and visual information. Tens of millions of Pinners (users) interact with the site every day by browsing, searching, Pinning, and clicking through to external sites...
Read moreData science
To meet the changing needs of the 450M+ people who use Pinterest, we have to know both how they’re using Pinterest today, and how they’ll be using it in the future.
To do this, our data science team has created a systematic approach, which gives us trustworthy conclusions that are both reproducible and automatable. We built tools that democratize the data, so engineers, product managers and designers can easily visualize and explore trends in content and experimental results. We also track how the world is changing as people modify their behaviors, diets, health routines, homes and interests. This gives us the knowledge we need to develop the revolutionary data-driven products our Pinners will be looking for next.
Scaling Pinterests ad corpus by 60x
In May 2020, Pinterest launched a partnership with Shopify that allowed merchants to easily upload their catalogs to the Pinterest platform and create Product Pins and shopping ads...
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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...
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Adventures in big data wonderland: Going down the Pinterest Path
Have you ever started looking for plants on Pinterest, only to end up shopping for pillows instead? Ever find yourself layers of Pins deep into finding a new idea, not sure of how you got there or where you started...
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Replication in Data Science: When is data science a house of cards?
As data scientists, when we reach an answer, we often communicate that answer and move on. But what happens when there are multiple data scientists with varying answers...
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Building Pinterest's A/B testing platform
As a data-driven company, we rely heavily on experiments to guide products and features. At any given time, we have around 1,000 experiments running, and we’re adding more every day...
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Pinterest Trends: Insights into the unstructured data.
What topics are Pinners interested in? When are they most engaged with these topics? How are they engaging with those topics...
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Skyline: ETL-as-a-service
Data plays a big role at Pinterest, in both enabling new product experiences for Pinners and providing insights into Pinner behavior...
Read moreFrom the Life at Pinterest Blog
Pinterest Engineering: Meet Nutsa Chichilidze from Dublin
Pinterest Engineering is growing in Dublin, so we sat down with Nutsa Chichilidze to learn more about her working life at Pinterest. From Pintern to full-time Software Engineer, get to know Nutsa’s journey and the invaluable benefits of joining the Pinterest team.
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Pinning Success for our incoming Pinterns
At Pinterest, fostering a supportive and inclusive environment is important to us. This commitment is displayed in our internship program with initiatives like “Pin Prep” and the “New Grad Buddy” program to set incoming interns up for success before they embark on their Pinterest journey.
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A night with Pinterest Engineering in Toronto
On March 11th, Pinterest Recruiting hosted “A night with Pinterest Engineering” in our Toronto office inviting guests to learn more about building an inspired and inclusive platform for users around the world. We’re excited to share a full recap and insight on how you can attend events like this
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Inspired to code: Jordyn Marcellus on joining Pinterest Canada
Pinterest Engineering is growing in Canada! What’s life at Pinterest like? Jordyn Marcellus, Software Engineer in Toronto, sat down with the Life at Pinterest Team to share their Pinterest journey, an inside scoop into engineering life in Canada and advice for those interested in joining the team.
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Life at Pinterest Profile: Aayush Mudgal
Meet Aayush Mudgal, Staff Machine Learning Engineer, and learn about his life at Pinterest.
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Pinterest Engineering: Meet Qiaochu Li
Our engineers are building an inspired and inclusive platform for Pinterest users worldwide. In the Pinterest Engineering series, you’ll meet the people behind the product, learn about their work and why they chose to grow their career with the Pinterest team.
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Pinterview Pro: Machine Learning
Become a Machine Learning Pinterview Pro with this exclusive guide from members of our Talent Acquisition team. They’ll share their favorite pieces of advice and recommendations for your interview prep and learning journey.
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Pinterest Engineering: Meet Lily Liu, Sr. Data Scientist
Our engineering team is building a more positive place online for Pinterest users around the globe. Each member of our team brings unique skill sets, perspectives and ideas to continue innovating and growing our product. What they all have in common…
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