Sr. Machine Learning Engineer

Pinterest Job Advertisements•Seattle, WA
•$270,400 - $332,012•Hybrid

About The Position

Build cutting-edge technology using advances in deep learning and machine learning to personalize Pinterest. Partner with teams across Pinterest to experiment with and improve machine learning models for product surfaces including Homefeed, Ads, Growth, Shopping, and Search, while learning how machine learning is applied across different areas. Use data-driven methods and the distinctive properties of Pinterest data to improve candidate retrieval. Work in a high-impact environment featuring rapid experimentation and product launches, and keep up with industry trends in recommendation systems. The position is hybrid from Pinterest’s Seattle, Washington office; part-time telecommuting is an option.

Requirements

  • Master’s degree (or foreign equivalent) in Computer Science, Business Analytics, Engineering (any field), or a closely related quantitative discipline.
  • Four years of experience in the job offered or in an occupation in a related field.
  • Four years of experience in user behavior modeling.
  • Four years of experience with recommender systems.
  • Four years of experience with machine-learning-based content personalization.
  • Four years of experience building large-scale data processing pipelines on Hadoop or Spark.
  • Four years of experience with large-scale machine learning systems.
  • Four years of experience presenting technical machine learning content to non-technical leaders.
  • Four years of experience developing large-scale ranking models.
  • Four years of experience orchestrating, executing, and analyzing large-scale A/B tests.
  • Four years of experience analyzing and modeling internet-scale graph structures.
  • Four years of experience developing large-scale machine learning models using TensorFlow or PyTorch.
  • Any suitable combination of education, training, and experience is acceptable.

Responsibilities

  • Build deep learning and machine learning technology to personalize Pinterest.
  • Partner with teams across Pinterest to experiment with and improve machine learning models for Homefeed, Ads, Growth, Shopping, and Search.
  • Use data-driven methods and Pinterest data to improve candidate retrieval.
  • Work in a high-impact environment with rapid experimentation and product launches.
  • Keep up with industry trends in recommendation systems.
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