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Pinterest

Staff Machine Learning Engineer, Monetization

Sorry, this job was removed at 10:22 a.m. (PST) on Friday, Nov 14, 2025
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In-Office
3 Locations
177K-364K Annually
In-Office
3 Locations
177K-364K Annually

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About 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.

Within the Ads Performance and Ads Delivery teams, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. Pinterest Machine Learning Engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 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.

We are currently hiring for multiple Staff Machine Learning Engineer roles across our Ads Machine Learning teams within Monetization Engineering. 

As a Staff Machine Learning Engineer, you will lead innovation across a spectrum of cutting-edge technologies vital to our advertising ecosystem, and drive the development of state-of-the-art applied machine learning systems. The scope of the work includes evolving our machine learning technology stack for ads ranking, building the next generation of scalable ads retrieval models, and powering discovery for millions of shoppers, and more. This is a high-impact opportunity to shape the future of Pinterest Shopping Ads, directly impacting user experience and advertiser success in a unique discovery-driven marketplace.  

What you’ll do:

  • Design features and build large-scale machine learning models to improve user ads action prediction with low latency
  • Drive innovation in personalized Shopping Ads recommendations through advanced modeling
  • Develop new methods for inferring user interests from online and offline activity
  • Mine text, visual, user signals to better understand user intention
  • Leverage multimodal signals (text, visual, user) to better understand user intent
  • Collaborate with product and sales teams to design and implement new ad products
  • Partner cross-functionally  with product, sales, data science, and engineering teams to design and improve user journey and optimize ads performance across all stages of retrieval and ranking

What we’re looking for:

  • MS or PhD degree in Computer Science, Statistics or related field; or equivalent experience
  • 6+ years of industry experience building production machine learning systems at scale, data mining, search, recommendations, and/or natural language processing
  • 2+ years of experience leading projects and mentoring team members
  • Strong mathematical skills with knowledge of statistical methods
  • Excellent written and verbal communication skills and strong cross-functional collaboration
  • Background in computational advertising is a plus, but not required

This position is not eligible for relocation assistance.



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At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only
$176,924$364,254 USD

Our Commitment to Inclusion:

Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.
 

Pinterest Seattle, Washington, USA Office

1730 Minor Ave, Seattle, Washington, United States, 98101

What you need to know about the Seattle Tech Scene

Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.

Key Facts About Seattle Tech

  • Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
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  • Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
  • Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Madrona, Fuse, Tola, Maveron
  • Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute

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