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Staff Machine Learning Engineer, Content Understanding

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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 understanding team, you will be responsible for developing horizontal knowledge graph and content 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, natural language processing, and multimodal modeling techniques to build 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 understanding, recommendation systems, information retrieval.
  • Experience with Generative AI and LLM.
  • Hands-on experience working with large scale ML modeling development and productization.
  • Effective collaborator working with cross functional partners and an excellent communicator.

Relocation Statement:

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

In-Office Requirement Statement:

  • We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
  • This role will need to be in the office for in-person collaboration 1 time per week and therefore needs to be in a commutable distance from our offices.


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
$166,694—$342,844 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, 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 an accommodation during the job application process, please notify for support.
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