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Engineering Manager, Shopping Content Mining at Pinterest (Toronto, ON, Canada)

About Pinterest: 

Pinterest is aiming to build a world-class shopping experience for our users, and has a unique advantage to succeed due to the high shopping intent of Pinners. The new Shopping Content Mining team being founded in Toronto plays a critical role in this journey. This team is responsible for building a brand new platform for mining and understanding product data, including extracting high quality product attributes from web pages and free texts that come from all major retailers across the world, mining product reviews and product relationships, product classification, etc. The rich product data generated by this platform is the foundation of the unified product catalog, which powers all shopping experiences at Pinterest (e.g., product search & recommendations, product detail page, shop the look, shopping ads).

There are unique technical challenges for this team: building large scale systems that can process billions of products, Machine Learning models that require few training examples to generate wrappers for web pages, NLP models that can extract information from free-texts, easy-to-use human labelling tools that generate high quality labeled data.Your work will have a huge impact on improving the shopping experience of 400M+ Pinners and driving revenue growth for Pinterest.

What youll do:

  • As the Engineering Manager, youll be responsible for:
    • Growing this team further in Toronto
    • Driving execution and deliver impact
    • Setting long term technical visions for this area
  • Work with tech leads to provide technical guidance on:
    • Large scale systems that can process billions of products
    • ML models for wrapper induction that require few training examples, NLP models for understanding free-texts
  • Drive cross functional collaborations with partner teams working on shopping

What were looking for:

  • 7+ years of industry experience, including 2+ years of management experience
  • Experience on large scale machine learning systems (full ML stack from modelling to deployment at scale.)
  • Experience with big data technologies (e.g., Hadoop/Spark) and scalable realtime systems that process stream data

Nice to have:

  • PhD in Machine Learning or related areas, publication on top ML conferences
  • Familiarity with information extraction techniques for web-pages and free-texts
  • Experience working with shopping data is a plus.
  • Experience building internal tools for labeling / diagnosing.

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