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Searching for your dream job? At LinkedIn, we strive to help our employees find passion and purpose. Join us in changing the way the world works. We are seeking extraordinary talent to help build sophisticated technology capable of serving billions of page views to over 550+ million LinkedIn members.
Feed Infrastructure (Feed Infra) is a large scale distributed systems that powers LinkedIn’s activity feed in homepage and is core to LinkedIn product. Our technology domain includes Information Retrieval, Machine Learning, and distributed datastore. It is composed of multiple business critical services including source of truth for activity data, indexes for timeline and a federation layer for second pass ranking.
Feed Infra is looking for a Sr Staff engineer to help define, and execute on next gen architecture for Feed Infra that can support agility on product innovations inside feed, and support running more complex models thereby creating huge impact for Feed ecosystem at LinkedIn. Ideal candidate should have strong experience in large scale & low latency distributed systems with a focus on operability, developer agility and relevance and proven track record of driving cross functional projects to completion. As a Sr. Staff Software Engineer, you will be a key technical leader and a role model within the Feed Infra organization. In this role, you will be responsible for working with Feed Infrastructure engineers, managers and partners to create the vision, technical roadmap and make it a reality.
A peek into unique challenges:
1. Scale – 10s of thousands of QPS, multiple terabytes of data, and running expensive scoring operations for millions of records per second.
2. Relevance – Our relevance partners experiment with hundreds of new ML models per quarter using thousands of features. Feed Infra needs to provide easy to use infrastructure to enable relevance engineers to experiment with novel solutions at a fast pace.
3. Product Agility – Feed Infra powers large number of use cases – Feed, Hashtags, QnA, Polls, Events and many others. It requires infra to provide capabilities to onboard new use cases quickly and enable product engineers to experiment new ideas with minimal friction.
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