Description

　　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.

　　Pinterest helps people Discover and Do the things they love. We have more than 500M monthly active users who actively curate an ecosystem of more than 400B Pins on more than 8B boards, creating a rich human curated graph of immense value.

　　Pinterest builds an internet scale personalized recommendation engine in 30+ languages, which requires a deep understanding of the users and content on our platform. As a staff machine learning engineer for the content/user understanding team, you will be responsible for developing horizontal knowledge graph and content/user understanding signals, from modeling to serving, and adopting them for various recommendation systems in Pinterest.

　　What you'll do:

　　Utilize state of the art machine learning, user modeling, natural language processing, and multimodal modeling techniques to build user/content signals that power personalized product experience across Pinterest ecosystems (discovery, growth, ads etc) Gather, examine, and integrate findings from data to build effective data-driven models. Partner with surface engineering teams and product team to discover opportunities to improve recommendation on Pinterest through content/user understanding Drive team level tech strategy, and solve complex problems independently

　　What we're looking for:

　　MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related fields 5+ years of industry experience in machine learning in industry and 1+ years of TL in use cases with large scale: content/user understanding, recommendation systems, information retrieval Hands-on experience working with large scale ML modeling development and productization. Effective collaborator working with cross functional partners and an excellent communicator Experience with Generative AI and LLM are a plus

　　Relocation Statement:

　　This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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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

　　$148,049-$304,496 USD

　　Our 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, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic under federal, state, or local law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require an accommodation during the job application process, please notify [email protected] for support.