Sr. Machine Learning Engineer, Content Shopping
PinterestAbout Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
With more than 535 million users around the world and 400 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,500 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.
The Content Shopping Mining ML team builds machine learning systems that understand shopping-related content across the web, turning unstructured merchant pages into high-quality structured product data like price, title, availability, and images. This helps improve product experiences on Pinterest, including content quality, distribution, recommendations, and search; for example, see the team’s KDD 2025 paper, Cross-Domain Web Information Extraction https://arxiv.org/pdf/2508.01096.
What you’ll do:
- Identify and evaluate high-value content sources for Pinterest including websites, merchants, and social media accounts
- Help build scalable systems to acquire that content and extract structured attributes from it.
- Partner closely with cross-functional teams across Pinterest to improve
Listed via
Greenhouse
Similar roles
Sr. Customer Support Engineer, Raipur
Danaher
Collibra Platform Developer (Mid to Senior)
Arch Capital Group Ltd.
Scheduling Director (Renewables Construction)
MasTec Industrial
Mom and Baby Care Manager - RN - Must reside in Nevada
CareSource
Design & Tech
Related reads from TCHNX
The Quiet Revolution in Local-First Software
As major platforms face outages and data breaches, a new generation of developers is building applications that prioritise local data storage and peer-to-peer sync, challenging the cloud-first orthodoxy that's dominated tech for two decades.
The Return of Physical Controls: Why Haptic Feedback Is Reshaping Digital Interfaces
After years of pursuing flat, buttonless designs, tech companies are rediscovering the value of tactile interaction. A new wave of products proves that touching isn't just feeling it's understanding.
The Quiet Revolution of Parametric Design Tools in Everyday Products
Parametric design is migrating from architecture studios to consumer products. As tools democratize and manufacturers adopt flexible production, we're entering an era of mass customization that challenges fundamental assumptions about design.