Manager II, Machine Learning Engineering, Monetization Engineering

San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US

Pinterest

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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 is one of the fastest growing online ad platforms, and our success depends on mining rich user interest data that helps us connect users with highly relevant advertisers / products. We’re looking for an Engineering Manager with experience in machine learning, data mining, recommender systems to lead a team that develop and execute a vision for the evolution of the machine learning technology stack for ads lightweight ranking models, ads retrieval candidate generation models, and/or ads engagement models.

In this role, you will be leading a world-class ML team on tackling new challenges, such as sequential recommenders for modeling user’s shopping journey, dedicated candidate generator to optimize for ads conversions, exploring model architectures beyond the traditional two-tower structure, etc., and leveraging LLMs to enhance our recommendation systems. As well as large CTR / conversion models, user sequence modeling, representation learning embeddings, new ads engagement objective modeling, GPU based retrieval, and many more to advance the ML models that power the ads engagement and delivery that bring together pinners and partners in this unique marketplace. 

 

What you’ll do:

  • Manage and grow the engineering team, providing technical vision and long-term roadmap development.
  • Design and build large-scale ML models to improve ads engagement prediction, ads retrieval and ranking efficiency & performance, 
  • Effectively collaborate and partner with several cross functional teams to build the next generation of lightweight ranking and engagement models, and/or ads retrieval candidate generation models, especially those related to conversion optimization.
  • Enable teams to do cross functional work with engineers from ranking/retrieval and ML infra teams.
  • Stay informed of emerging ML research and industry trends, identify relevant techniques, and inspire the team in evaluating and incorporating these approaches.
  • Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.

 

What we’re looking for:

  • M.S. or Ph.D. in Computer Science, Machine Learning, or a related field.
  • 6+ years of industry experience in building production machine learning systems at scale, data mining, search, recommendations, with related background in recommender systems, ranking/retrieval or representation learning domains
  • 1-2 years of experience managing engineering teams as a TLM or EM cross-functional collaborator and strong communicator
  • Hands-on experience with large-scale online ranking/recommendation systems.
  • Ads domain experience is a plus.

 

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 once a week and therefore needs to be in a commutable distance from one of the following offices: San Francisco / Palo Alto / Seattle.

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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$208,145—$364,254 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 a medical or religious accommodation during the job application process, please complete this form for support.
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Tags: Architecture Computer Science Data Mining Engineering GPU LLMs Machine Learning ML models Recommender systems Research

Perks/benefits: Career development Equity / stock options Flex hours Transparency

Region: North America
Country: United States

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