Within the Ads Ranking team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack for Ads Ranking, including Lightweight Ranker, Engagement Modeling, and Conversion Modeling. You will work on tackling new challenges in Ads Ranking, such as user sequence modeling, large models, embedding features, model quantization, utility alignment, application of LLM and multi-modal models, as well as domain-specific challenges like next-gen lightweight ranking beyond two-tower architecture, quota allocation, new engagement type modeling, RoAS optimization and many more to advance the ML models that power the ads ranking stage and delivery that bring together pinners and partners in this unique marketplace.
What you’ll do:
- Be responsible for the development of state-of-the-art applied machine learning projects for one of the 3 modeling problems in ads ranking: lightweight ranker, engagement modeling and conversion modeling
- Design features and build large-scale machine learning models to improve user ads action prediction with low latency
- Develop new techniques for inferring user interests from online and offline activity
- Mine text, visual, user signals to better understand user intention
- Work with product and sales teams to design and implement new ad products
What we’re looking for:
- MS or PhD degree in Computer Science, Statistics or related field
- 6+ years of industry experience building production machine learning systems at scale, data mining, search, recommendations, and/or natural language processing
- 2+ years of experience leading projects/teams
- Strong mathematical skills with knowledge of statistical methods
- Cross-functional collaborator and strong communicator
- Background in computational advertising is preferred, but not required
This position is not eligible for relocation assistance.
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