Sr. Software Engineer, Systems Infrastructure

LinkedIn•Bellevue, WA

21h•$139,000 - $229,000•Hybrid

About The Position

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. Bring your experience in distributed systems and algorithms and a strong systems orientation (multi-threading, concurrency, scalability, performance). You should understand frameworks for caching, queuing, and distributed data storage, and be excited to work on cutting edge open-source systems.

Requirements

BA/BS Degree in Computer Science or related technical discipline, or related practical experience.
2+ years of industry experience in software design, development, and algorithm related solutions.
2+ years experience programming in object-oriented languages such as Java, C++, Python, Go, Rust, C# and/or Functional languages such as Scala or other relevant coding languages
Hands on experience developing distributed systems, large-scale systems, databases and/or Backend APIs

Nice To Haves

BS and 5+ years of relevant work experience, MS and 4+ years of relevant work experience, or PhD and 2+ years of relevant work experience
Experience in architecting, building, and running large-scale distributed systems
Experience with industry, opensource, and/or academic research in technologies such as Hadoop, Spark, Kubernetes, Feather, GraphQL, GRPC, Apache Kafka, Pinot, Samza or Venice
Experience with open-source project management and governance
Data Structures & Algorithms
Distributed Systems
Operating Systems
Cloud Computing

Responsibilities

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 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.