#pinterest

Pinterest Engineering 27 Jul 2026 13 min read

Part 1 of 2 Authors Personalization (Homefeed): Yuke Yan, Chuxi Wang, Andreanne Lemay, Olafur Gudmundsson, Anna Kiyantseva, Krystal Benitez, Jongho Kim, Jiacong He, Rahul Goutam, James Li, Dylan Wang User Understanding: Simin Li, Sufyan Suliman, Yingjian Ding, Hongbo Deng Data Science: Armando Ordorica, Yan Chen, Ellie Zhang, Karim Wahba Introduction Pinterest’s mission is to help people discover the inspiration to…

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Pinterest Engineering 22 Jul 2026 6 min read

Ammar Ekbote | Senior Software Engineer Chan Kim | Senior Software Engineer Managing Infrastructure as Code (IaC) across a massive organization comes with a unique set of security and logistical challenges, particularly when operating within a distributed, multi-repository architecture. At Pinterest, we designed the Resource Provisioner Pipeline (RPP) , our specialized, proprietary Terraform execution engine to safely manage both critical…

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Pinterest Engineering 25 Jun 2026 10 min read

Sheng Huang | Software Engineer, AI Platform; Pong Eksombatchai | Machine Learning Engineer, Applied Sciences; Saurabh Vishwas Joshi | Software Engineer, AI Platform; Gaurav Arora | Software Engineer, AI Platform; Karthik Anantha Padmanabhan | Engineering Director, AI Platform At Pinterest, foundation models power recommendations for over 600 million monthly active users. Our latest Foundation Model (ACM RecSys 2025) pre-trains on…

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Pinterest Engineering 24 Jun 2026 11 min read

Yisheng Zhou | Software Engineer II Liang Mou | Sr Staff Software Engineer Gabriel Raphael Garcia Montoya | Staff Software Engineer Istvan Podor | Staff Software Engineer Introduction In the first post of this series , we introduced Pinterest’s next-generation CDC-based ingestion platform built on Kafka, Flink, Spark, and Iceberg. In production, upstream schemas are constantly evolving, and in a…

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Pinterest Engineering 21 May 2026 12 min read

Authors ( listed alphabetically ) Ads Feature Engineering Infra team: Ajay Venkatakrishnan, Le Zhang Core ML Infra team: Eric Shang, Pihui Wei ML Data team: Connor Votroubek, Yi He User Understanding team: Camilo Munoz, Simin Li If you work on ranking, retrieval, or recommendation systems, you’ve probably asked for some version of the same thing: “Give me the last N…

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Pinterest Engineering 12 May 2026 4 min read

An Engineer’s Guide to Better AI Skills: Implementing a Testing Process to Optimize Agent Performance in Any Repository or Skill Author: Daniel Reed The tech industry is currently seeing a massive overhaul in the way we work and many are enjoying the benefits of AI agents, particularly when automating engineer workflows and serving domain-specific knowledge. However, relying on agents to…

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Pinterest Engineering 8 May 2026 5 min read

Huiqin Xin | Machine Learning Engineer II, Ads Vertical Modeling; Lakshmi Manoharan | Senior Machine Learning Engineer, Ads Vertical Modeling; Karthik Jayasurya | Staff Machine Learning Engineer, Ads Signals; Ziwei Guo | Senior Machine Learning Engineer, Ads Vertical Modeling; Alina Liviniuk | Machine Learning Engineer II, Ads Vertical Modeling Motivation: The Need for Real-Time Context In a previous post ,…

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Pinterest Engineering 1 May 2026 16 min read

Guangtong Bai | Staff Software Engineer, Product ML Infrastructure*; Shantam Shorewala | Software Engineer II, Product ML Infrastructure*; Chi Zhang | Staff Software Engineer, AI Platform*; Neha Upadhyay | Software Engineer II, AI Platform*; Haoyang Li | Director, Product ML Infrastructure *These authors contributed equally to this article. Background At Pinterest, our online ML serving systems employ a root-leaf architecture.…

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Pinterest Engineering 27 Apr 2026 7 min read

Authors: Richard Huang | Machine Learning Engineer II; Yu Liu | Senior Machine Learning Engineer; Ziwei Guo | Senior Machine Learning Engineer; Andy Mao | Staff Machine Learning Engineer; Supeng Ge | Sr. Staff Machine Learning Engineer Introduction At Pinterest, conversion ads are crucial for matching users with products they are likely to purchase, boosting value for both users and…

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Pinterest Engineering 20 Apr 2026 10 min read

Shanhai Liao | Senior Software Engineer, Content Acquisition and Media Platform; Di Ruan, | Senior Staff Software Engineer, Content Acquisition and Media Platform; Evan Li, | Senior Engineering Manager, Content Acquisition and Media Platform Introduction Accurate content understanding underpins Pinterest’s ability to drive distribution and engagement. This requires deep insight not just into the image itself, but also the outbound…

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Pinterest Engineering 15 Apr 2026 14 min read

Vaibhav Shankar; Staff Software Engineer | Raymond Lee; Staff Software Engineer | Chia-Wei Chen; Staff Software Engineer | Shunyao Li; Sr. Software Engineer | Yi Li; Staff Software Engineer | Ambud Sharma; Principal Engineer | Saurabh Vishwas Joshi; Principal Engineer | Charles-A. Francisco; Senior Engineer | Karthik Anantha Padmanabhan; Director, Engineering | David Westbrook; Sr. Manager, Engineering One day in…

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Pinterest Engineering 13 Apr 2026 8 min read

Authors: Matt Lawhon | Sr. Machine Learning Engineer; Filip Ryzner | Machine Learning Engineer II; Kousik Rajesh | Machine Learning Engineer II; Chen Yang | Sr. Staff Machine Learning Engineer; Saurabh Vishwas Joshi | Principal Engineer At Pinterest, scaling our recommendation models delivers outsized impact on the quality of the content we serve to users. Our Foundation Model (oral spotlight,…

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Pinterest Engineering 8 Apr 2026 3 min read

Author: Lin Wang (Android Performance Engineer) Default Feature For mobile apps, performance is considered as the “default feature”, which means apps are expected to run fast and be responsive. It’s just as if we expect a watch to show the time. With no exceptions at Pinterest, we measure, protect and improve performance for all of our key user experiences’ surfaces,…

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Pinterest Engineering 7 Apr 2026 9 min read

Homefeed: Jiacong He, Dafang He, Jie Cheng (former), Andreanne Lemay, Mostafa Keikha, Rahul Goutam, Dhruvil Deven Badani, Dylan Wang Content Quality: Jianing Sun, Qinglong Zeng ML Serving: Li Tang Introduction In feed recommendation, we recommend a list of items for the user to consume. It’s typically handled separately from the ranking model where we give probability predictions of user-item pairs.…

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