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Machine Learning Engineer, Shopping Discovery

 

Machine Learning Engineer, Shopping Discovery

San Francisco | California | United States

Shopping is at the core of Pinterest’s mission to help people create a life they love. Every day hundreds of millions of users (Pinners) come on Pinterest to find inspiration to decorate their home, to wear outfits on different occasions, host parties and various other things to create a better life. Those inspirations are visual and reflect very detailed tastes of the Pinners regarding the choice of color, style, etc. The shopping team is responsible for connecting inspirations to products that Pinners would like to buy and create a life they love. Connecting inspiration to product is very challenging and requires an understanding of user preferences, the content of the image, visual matching of images and selecting and ranking the top images based on various signals. More interestingly, we need to solve these challenges at the awe-inspiring scale of Pinterest for 300M+ users, tens of billions of inspiration pins and hundreds of millions of products. The team is using one of the most sophisticated computer vision techniques for image matching, deep learning for user understanding and ranking at the scale unimaginable at most places. If you are excited to improve lives using the magic of AI/ML at a very large scale then you must consider this position.

What will this person do?

  • Use machine learning, natural language processing, computer vision and graph analysis to solve a mix of modeling and ranking problems involving matching inspirations to users and products
  • Research and develop machine learning models that understand and classify Internet-scale contents
  • Research and develop models to understand users’ shopping intent and enable personalization
  • Develop processes to effectively evaluate product ranking quality and impact on Pinner experiences
  • Run experiments to generate and confirm hypotheses to improve key quality metrics
  • Use Big Data technologies (such as Hadoop, Spark, Storm) for building large scale data mining pipelines

What type of experience is required?

  • Ph.D. and 3-5 years of experience or Master's and 5-10 years of experience
  • Solid hands-on experience in machine learning the context of search, recommendation systems, e-commerce or other consumer internet products
  • Experience in working as a tech lead in large scale machine learning projects
  • Over 4 years of experience with algorithms, data structures, and coding
  • Work with engineers and technical program managers to define technical strategy and roadmap
  • Collaborate with cross-functional product and engineering teams to understand requirements and incorporate them in the roadmap
  • Understanding of an object-oriented programming language (Java, C++, Python)
  • Experience in MapReduce/Hadoop and/or distributed systems

What skills are ideal?

  • Ph.D. in an area of Machine Learning
  • Experience as a tech lead for 5+ team of ML Engineers
  • Experience with large scale Search or Recommendation algorithms

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