Sr. Staff Software Engineer, Compute Infrastructure

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 Sr. 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 will touch every aspect of our engineering organization. We are looking for experienced 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 experienced engineers, including distinguished engineers and technical fellows, 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

• You will directly contribute to LinkedIn’s Compute infrastructure strategy.
• You will build and operate a platform that allocates hardware resources with necessary physical/logical distribution for fault tolerance and easy maintenance.
• 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 help up-level and coach a large team of talented developers.

Qualifications

Basic Qualifications

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

Preferred Qualifications

• 10+ years of experience in software design, development, and algorithm related solutions with at least 5 years of experience in a technical leadership position
• 10+ years of programming experience in an object-oriented programming language such as Go, Java, C/C++, Rust
• 5+ years of experience building large-scale compute infrastructure, and distributed systems
• Demonstrated understanding of operating system fundamentals, container technologies, and systems knowledge.
• Experienced in leading technical teams and mentoring other engineers
• Experience building and operating cluster management solutions such as Kubernetes.
• Experience with IaaS systems and capacity management.
• Experience with networking and security principles.
• Deep understanding of Kubernetes architecture and key components (API server, scheduler, kubelet, etc.), with a proven track record of deploying, managing, and troubleshooting Kubernetes clusters.
• Strong proficiency in Golang, as it is the primary language.
• Solid understanding of networking concepts relevant to Kubernetes, including CNI plugins and pod networking.
• Knowledge of Kubernetes security best practices such as RBAC, network policies, and Pod security policies.
• Proficiency with monitoring and logging tools such as Prometheus, Grafana, and Fluentd.

Suggested Skills

• Distributed Systems
• Kubernetes
• Technical Leadership

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $198,000 to $326,000. 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.

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.

LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.

If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation.

Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:

• 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.

San Francisco Fair Chance Ordinance ​

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

Pay Transparency Policy Statement ​

As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.

Global Data Privacy Notice for Job Candidates ​

Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.