Manager II, Machine Learning Engineering, Ads Signals

The Ads Signal team builds ML signals to improve advertising performance and solve various business problems. The team is responsible for developing and innovating ML signals, integrating them to production models, and building toolings to improve signal development lifecycle. You will lead a group of ML talents to innovate our representation learning and model pre-training techniques, leveraging sequence/graph and cross domain datasets. These will further power our ranking and retrieval models to improve ads performance. In short, this is a unique position, where you'll get the freedom to chart your own journey and advance Pinterest ML with state of the art techniques.

What you'll do:

• Provide technical vision and define the long-term roadmap in representation learning and model pre-training areas.
• Stay informed of emerging ML research and industry trends, identify relevant techniques, and inspire the team in evaluating and incorporating these approaches.
• Oversee the model and signal development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.
• Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.
• Collaborate with cross functional application teams, enable teams to do cross functional work with engineers from ranking/retrieval and ML infra teams.

What we're looking for:

• MS or PhD degree in Computer Science, Statistics or related field
• 6+ years of industry experience with related background in Recommender Systems, Ads Ranking/Retrieval or Representation Learning domains.
• 2+ years of experience as TLM or EM managing engineering teams
• Strong software engineering and mathematical skills with knowledge of machine learning
• Hands-on experience with large-scale online ranking/recommendation systems.
• Experience with Ads domain is a plus.

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

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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