Job Description

This role will be available in Bellevue, Washington.

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

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.

What You'll Do:

The ideal 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 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.

Qualifications

Basic Qualifications

• 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# or functional languages such as Scala or other relevant coding languages
• Hands on experience developing distributed systems, large-scale systems, databases or Backend APIs

Preferred Qualifications

• 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

Suggested Skills:

• Data Structures & Algorithms
• Distributed Systems
• Operating Systems
• Cloud Computing

You will Benefit from our Culture:

We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $139,000 to $229,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.

The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits.

Additional Information