About Pinterest:

Millions of people across the world come to Pinterest to find new ideas every day. Its 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, youll be challenged to take on work that upholds this mission and pushes Pinterest forward. Youll 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.

Shopping is at the core of Pinterests mission to help people create a life they love. The shopping discovery team at Pinterest is inventing a brand new, more visual and personalized shopping experience for 350M+ users worldwide. The team is responsible for delivering mid-funnel shopping experience on shopping surfaces like Product Detail Page, Shopping Search, Shopping on Board etc. As an engineer of the team you will be working on the most cutting edge recommendation algorithms to develop diverse types of shopping recommendations that will be displayed across different shopping surfaces on Pinterest. 

Youll also be responsible for optimizing the whole page layout by appropriately selecting and slotting the UI templates and recommendation modules optimizing towards a shopping metric. As an engineer of the team youll be running experiments and directly improving the shopping metrics contributing to the bottom line of the company.

If you are excited about large scale machine learning problems in the area of recommendation, search and whole page optimization then you must consider this role

What you'll do: 

• Develop large scale shopping recommendation algorithms
• Build data pipelines to do data analysis and collect training data
• Train deep learning models to improve quality and engagement of shopping recommenders
• Work on backend and infrastructure to build, deploy and serve machine learning models
• Develop algorithms to optimize the whole page layout of the shopping surfaces
• Drive the roadmap for next generation of shopping recommenders

What we're looking for: 

• 3+ years working experience in the area of applied Machine Learning
• Interest or experience working on a large-scale search, recommendation and ranking problems
• Interest and experience in doing full stack ML, including backend and ML infrastructure
• Experience is any of the following areas
  
  • Developing large scale recommender systems
  • Contextual bandit algorithms
  • Reinforcement learning

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