Machine Learning Engineer, Content Signals

Toronto, CA

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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.

Within the Content Signals team, you’ll be responsible for building machine learning signals from NLP and CV components to productionizing the end product in batch and real-time setting at Pinterest scale. Our systems offer rich semantics to the recommendation platform and enable the product engineers to build deeper experiences to further engage Pinners. In understanding structured and unstructured content, we leverage embeddings, supervised and semi-supervised learning and LSH. To scale our systems we leverage Spark, Flink and low-latency model serving infrastructure.

What you’ll do:

  • Apply machine learning approached to build rich signals that enable ranking and product engineers to build deeper experiences to further engage Pinners
  • Own, improve, and scale signals over both structured and unstructured content that bring tens of millions of rich content to Pinterest each day
  • Drive the roadmap for next generation content signals that improve content ecosystem at Pinterest
  • Work in a fast-paced environment with a quick cadence of research, experimentation, and product launches

What we’re looking for:

  • 5+ years of relevant industry experience 
  • Deep expertise in content modeling at consumer Internet scale
  • Strong ability to work cross functionally and with partner engineering teams
  • Expert in Java, Scala or Python

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Job tags: Engineering Java Machine Learning NLP Python Research Scala Spark