LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover opportunities, and gain insights. Our global reach means we get to make a direct impact on the world's workforce in ways no other company can. We're much more than a digital resume - we transform lives through innovative products and technology.
We're building the next-generation data infrastructure, including storage, streams, media and analytics platforms. Help us scale LinkedIn infrastructure to handle massive data growth across the LinkedIn ecosystem as we experience dramatic growth in membership and products. You will utilize distributed systems and algorithms and perfect your strong systems orientation skills (multi-threading, concurrency, scalability, performance). You will understand frameworks for caching, queuing, and distributed data storage, and be excited to work on cutting edge open-source systems.
The ideal intern candidate will help scale LinkedIn's infrastructure to handle massive growth in membership, traffic, and data as we continue to experience dramatic growth in the usage of our products with focus in one or more of the areas below:
Data Infrastructure: A focus on building and supporting large scale systems(e. . Kafka, Espresso, Voldemort, Pinot, Helix, Ambry, Hadoop etc. ) and tools that enable the generation of insights and data products on all of LinkedIn's internal and external data via self-serve computing, reporting solutions, and interactive querying
Search, Networks and Analytics: Build and operate the platform that powers all of search at LinkedIn-responding to thousands of queries per second with target latencies in tens of milliseconds. The goal is to provide and run in 24/7 production environment a platform that enables search quality engineers to rapidly innovate, experiment and improve relevance-while at the same time remaining constantly available and performant to our users
Service: Provide the technical platform for all of LinkedIn Engineering to build services, which are the essential unit of development and deployment
Content and Community: Deliver the systems and algorithms that generate and serve feeds of professionally relevant activities and content
Basic Requirements: - You must be currently enrolled in a college or university program and must be returning to school the term following your summer internship - Currently pursuing a B. . or higher in computer science or related technical discipline
Preferred Qualifications: - Experience building distributed, Internet-scale systems - Experience building and applying frameworks for one or more of the following: caching, queuing, RPC, parallelism, and/or distributed knowledge - Thorough knowledge of multi-threading, concurrency, parallel processing and distributed computing technologies - Experience with industry, open-source projects and/or academic research in large-data, parallel and distributed systems
A little about us:
LinkedIn's vision is to create economic opportunity for every member of the global workforce. Our employee talent is our #1 operating priority.