Sr. Machine Learning Engineer

Pinterest Job Advertisements•San Francisco, CA
•$249,600 - $332,012•Hybrid

About The Position

Build cutting-edge technology using the latest advances in deep learning and machine learning. Partner with teams across the company to experiment with and improve machine learning models for product surfaces including Homefeed, Ads, Growth, Shopping, and Search. Use data-driven methods and the unique properties of Pinterest data to improve candidate retrieval. Work in a high-impact environment with quick experimentation and product launches, keep up with industry trends in recommendation systems, and leverage LLMs to enhance content understanding. Partial telecommuting is permitted from within a commutable distance.

Requirements

  • Master's degree in Electrical Engineering, Computer Science, or a related field.
  • Three years of experience in the job offered or a related position.
  • Three years of experience using C++, Python, Java, and SQL for production services and data analysis.
  • Three years of experience with databases and distributed storage, including distributed relational systems.
  • Three years of experience with Large Language Models (LLMs).
  • Three years of experience with approximate nearest neighbor (ANN) search.
  • Three years of experience with recommender systems, search systems, and ads systems.
  • Three years of experience with Spark.
  • Three years of experience with Airflow.
  • Three years of experience with Kubernetes.
  • Three years of experience with A/B testing.
  • Three years of experience with PyTorch.
  • Three years of experience with information retrieval.

Responsibilities

  • Build technology using advances in deep learning and machine learning.
  • Partner with teams across the company to experiment with and improve machine learning models for Homefeed, Ads, Growth, Shopping, and Search.
  • Use data-driven methods and the unique properties of Pinterest data to improve candidate retrieval.
  • Participate in quick experimentation and product launches in a high-impact environment.
  • Keep up with industry trends in recommendation systems.
  • Leverage LLMs to enhance content understanding.
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