Principal Staff Software Engineer - Compute Infrastructure

Company Description

LinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed.

Join us to transform the way the world works.

Job Description

This role will be based in Mountain View, CA

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.

As a Principal Staff Software Engineer of the Compute Infrastructure team at LinkedIn, you will play a crucial role in our ongoing efforts to re-architect our compute infrastructure stack. This is a high-profile, high-impact project that touches every aspect of our engineering organization. We are looking for professionals who have a proven track record of designing large-scale compute infrastructure and driving consensus.

In this role, you will design and implement solutions that enable LinkedIn to scale its compute infrastructure to meet the demands of a rapidly growing user base. This will involve working closely with a team of engineers to develop and operate solutions that are robust, scalable, and efficient. You will also need to work collaboratively with cross-functional teams and be comfortable operating in a fast-paced, dynamic environment.

If you are passionate about building the underlying technology that powers one of the world's most-used internet applications, and have the skills and experience to help us take our compute infrastructure to the next level, we want to hear from you. Apply now to join our team and help shape the future of LinkedIn.

Responsibilities:

• Define the multi-year technical vision for LinkedIn's compute platform, translating company-level priorities into an infrastructure architecture and roadmap.

• You will build and operate world class high performance scheduling/deployment solutions including some of the world's largest Kubernetes clusters to place stateless/stateful services, ML workloads and short running jobs efficiently.

• You will build and operate a platform that allocates hardware resources with necessary physical/logical distribution for fault tolerance and easy maintenance.

• Build alignment across the engineering organization on infrastructure direction, partnering with distinguished engineers, fellows, and senior leadership

• Elevate engineering quality org-wide by coaching senior engineers, setting technical standards, and shaping how infrastructure decisions are made at LinkedIn

Qualifications

Basic Qualifications 

• BS/BA in Computer Science or related technical field or equivalent technical experience
• 10+ years of industry experience in software design, development, and algorithm related solutions
• 10+ years of experience programming in object-oriented languages such as Java, Go, C/C++, Rust, Rust, Python
• Experience developing large-scale distributed systems
• 4+ years of experience as an architect, or technical leadership position
• Experience developing large-scale distributed systems and using agentic software engineering
   

Preferred Qualifications

• 15+ years of experience in software design, development, and algorithm related solutions
• 15+ years of programming experience in an object-oriented programming language such as Go, Java, C/C++, Rust
• 5+ years of experience in a technical leadership position
• 5+ years of experience building large-scale compute infrastructure, and distributed systems
• Demonstrated understanding of operating system fundamentals, container technologies, and systems knowledge. 
• Experience building and operating cluster management solutions such as Kubernetes.
• Experience with IaaS systems and capacity management.
• Experience with networking and security principles.
• Experience in leading technical teams and mentoring other engineers

Suggested Skills

• Distributed Systems
• Kubernetes
• Golang
• Technical Leadership

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $231,000 to $378,000. 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

Equal Opportunity Statement 

We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

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• Documents in alternate formats or read aloud to you
• Having interviews in an accessible location
• Being accompanied by a service dog
• Having a sign language interpreter present for the interview

A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.

LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.

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Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.

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