Staff Machine Learning Engineer, Ads Candidate Generation

About Pinterest:  Millions of people across the world come to Pinterest to find new ideas every day. It’s where they get inspiration, dream about new possibilities and plan for what matters most. Our mission is to help those people find their inspiration and create a life they love. In your role, you’ll be challenged to take on work that upholds this mission and pushes Pinterest forward. You’ll grow as a person and leader in your field, all the while helping Pinners make their lives better in the positive corner of the internet.Creating a life you love also means finding a career that celebrates the unique perspectives and experiences that you bring. As you read through the expectations of the position, consider how your skills and experiences may complement the responsibilities of the role. We encourage you to think through your relevant and transferable skills from prior experiences.Our new progressive work model is called PinFlex, a term that’s uniquely Pinterest to describe our flexible approach to living and working. Visit our PinFlex landing page to learn more. Within the Ads candidate generation team, our mission is to bridge the gap between the aspirations of Pinners and the products offered by our partners. In this role, you will spearhead the developing and executing a visionary strategy to evolve our machine learning technology stack for Candidate Generators. You'll tackle cutting-edge challenges, including managing an ever-growing corpus of billions of shopping ads, exploring model architectures beyond the traditional two-tower structure, modeling users’ long-short interests, and implementing sequential transducers for generative recommendations. Additionally, you'll leverage large language models (LLMs) to enhance our recommendation systems and optimize dynamic quota allocation. Your work will be instrumental in advancing the ML models that form the backbone of our ads retrieval and delivery processes, effectively connecting Pinners with our partners' offerings in this unique marketplace.What you’ll do:Be responsible for the development of state-of-the-art applied machine learning projects for ads candidate generation models GPU-based ads retrieval system that extends beyond the traditional two-towers model architecture.Develop a unified retrieval model that leverages both organic and ad-related labels, as well as attributed conversion labels, to create a scenario-adaptive retrieval model.Collaborate with the team to explore opportunities for leveraging LLMs to enhance recommendation quality.What we’re looking for:MS or PhD degree in Computer Science, Statistics or related field6+ years of industry experience building large scale production recommendation or search systems2+ years of experience leading projects/teamsStrong mathematical skills with knowledge of statistical methodsCross-functional collaborator and strong communicatorExperience in computational advertising is highly desirable, though not requiredExperience in advanced retrieval modeling is highly desirable, though not requiredExpertise in GPU model performance profiling and optimization is highly desirable, though not requiredExperience in utilizing large language models within production recommendation systems is highly desirable, though not requiredThis position is not eligible for relocation assistance.#LI-HYBRID#LI-SM4Our Commitment to Diversity: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.