Machine Learning Engineer, Shopping Content Mining

Toronto, ON

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Posted 1 week ago

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. As a Pinterest employee, 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 users make their lives better in the positive corner of the internet.

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 you’ll do:

  • As a ML engineer, you will design and build large scale ML 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 we’re looking for:

  • 3+ years of industry experience
  • Hands-on experience on large scale machine learning systems (full ML stack from modelling to deployment at scale.)
  • Hands-on 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

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Job tags: Big Data Hadoop Machine Learning ML NLP Spark