Job Description

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 the conversion modeling team. You will work on tackling new challenges such as user sequence modeling, embedding features, model quantization, utility alignment, RoAS optimization and many more to advance the ML models that power the heavy ranker stage and delivery that bring together pinners and partners in this unique marketplace.
What you'll do:

• Execute the development of state-of-the-art applied machine learning projects for the ads conversion modeling team
• Coach and mentor engineers for the conversion modeling team
• 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 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
• 3+ years of industry experience building large-scale machine learning models, with experience in ranking and recommender systems (e.g., search, recommendations, personalization).
• Strong mathematical skills with knowledge of statistical methods
• Cross-functional collaborator and strong communicator
• Background in computational advertising is preferred, but not required

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 1-2 times/quarter and therefore can be situated anywhere in the provinces of Ontario or British Columbia.

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Skills Required