Pinterest helps people discover the things they love, and inspires them to go do those things in their daily lives. 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. More than 45% of pins seen anywhere on Pinterest are recommended by the Related Pins backend. See our WWW 2017 paper for further technical details.
In 2020, Related Pins takes on a new initiative to improve user session experience and optimize for downstream engagements. Our goal is to leverage cutting edge machine learning technologies to personalize the recommendation feed through diversification, click shaping, etc, to maximize the downstream impact. On this project, you will work with a group of friendly and experienced ML engineers on the full cycle of ML ranking for the Related Pins recommendation system, build the next generation ML ranking solutions to optimize the total session engagement on closeup, including bringing in personalized recommendations, diversifying user traffic, and scaling ranking infrastructure.
What you’ll do:
What we’re looking for:
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