Machine Learning Engineer, Related Pins

San Francisco

Pinterest brings millions of people the inspiration to create a life they love for everything; whether that be tonight’s dinner, next summer’s vacation, or a dream house down the road. Related Pins, a.k.a. “More Like This” is one of the largest content surfaces across Pinterest. It helps user exploration by recommending other content related to an initial pin and the user context, often helping Pinners discover the content they love but can’t quite describe in words. We’re looking for someone who will work on the full cycle of ML ranking for the Related Pins recommendation system. The goal is to leverage the cutting edge technologies in machine learning and deep learning to find high-quality content that is related to the current closeup pin.


What you’ll do :
  • Work with a group of friendly and experienced ML engineers to build the next generation ML ranking solutions to improve the user experience on closeup, including bringing in personalized recommendations, improving ranking quality, and scaling ranking infrastructure.
  • Design and develop machine learning models to predict user’s intent on the closeup and enable personalized content retrieval in candidate generation.
  • Partner closely with other product teams, including Shopping, Content, Trust & Safety, to experiment with different algorithms and validate their effectiveness, while gaining knowledge of how ML works in all these products.
  • Use Big Data technologies (such as Hadoop, Spark, Storm) for building large scale data mining pipelines and identify product opportunities.
  • Develop processes and conduct live experiments to effectively evaluate ranking quality and impact on Pinner experiences.
What we’re looking for :
  • Ph.D. with 3+ years or Masters with 5+ years of software engineering/ML expertise and the ability to build scalable recommendation systems
  • Hands-on experience in content retrieval, personalized ranking, and user intent prediction.
  • Practical experience in machine learning, deep learning or information retrieval.
  • Experience in working with cross-functional product and engineering teams to understand requirements and incorporate them in the roadmap
  • Experience in working with large code bases, cross-team collaboration, mentoring other engineers, giving and getting feedback, and reviewing code/systems.
  • Experience with MapReduce/Hadoop and/or distributed systems.

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