Staff Machine Learning Engineer, Monetization

Pinterest•Palo Alto, CA

1d•Hybrid

About The Position

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 our Ads Performance and Ads Delivery teams, we connect the dots between what Pinners aspire to do and the products our advertising partners offer—building personalized, discovery-driven experiences that help people create a life they love. Pinterest is just over 4,000 employees globally, which means our teams stay small, high-ownership, and fast-moving, with hands-on access to an exceptional vault of data and the chance to build and evolve large-scale recommendation and ranking systems at real-world scale. We’re hiring multiple Staff Machine Learning Engineers across our Ads Machine Learning org within Monetization Engineering. In this role, you’ll lead innovation across core applied ML and marketplace technologies that power our ads ecosystem—advancing our ads ranking stack, building the next generation of scalable ads retrieval models, and improving shopping discovery for millions of users. You’ll also help shape the evolution of the Pinterest marketplace by designing systems and experiments that improve the ads delivery funnel, inform the utility function, and influence auction mechanisms and ad allocation—using deep analysis of marketplace dynamics to unlock new insights. Overall, this is a high-impact opportunity to define what great looks like for Pinterest Shopping Ads, directly improving both user experience and advertiser outcomes in a uniquely discovery-first marketplace.

Requirements

Degree in Computer Science, Machine Learning, Statistics or related field
Experience building production machine learning systems at scale, data mining, search, recommendations, and/or natural language processing
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

Nice To Haves

Background in computational advertising is a plus, but not required

Responsibilities

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
Build and improve backend systems and statistical models that underlay the marketplace to maximize value for Pinners, Partners and Pinterest.
Define and implement experiments to understand long term Marketplace effects
Develop strategies to balance long and short term business objectives.
Drive multi-functional collaboration with peers and partners across the company to improve knowledge of marketplace design and operations.