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LinkedIn Sr. Software Engineer - Compute Infra (Kubernetes) in Mountain View, California

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.

At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together.

This role will be based in Mountain View, CA.

In the Compute Infrastructure SRE team at LinkedIn, you will be charged with building the next-generation infrastructure and platforms for LinkedIn. This is a unique opportunity to work on a high-profile, high-impact ongoing project that will touch every aspect of our engineering organization. Specifically, the LinkedIn Kubernetes Infrastructure team provides an on-premises Kubernetes platform for the entire company. The team provides capability to efficiently create Kubernetes clusters on-demand, scale the clusters beyond the current industry limits, automate upgrades, and intelligently detect and remediate cluster health, etc.

In this role, you will have the opportunity to enable LinkedIn to scale its Compute Infrastructure to meet the demands of a rapidly growing user base. This will involve working closely with cross functional teams and be comfortable operating in a fast-paced, dynamic environment.

Responsibilities

· Serve as a primary point responsible for the overall health, performance and capacity of the

Kubernetes cluster management platform.

· Develop tools and infra to support the entire Linkedin's stateless and stateful apps from the

existing compute pools onto Kubernetes clusters.

· Manage site critical private cloud infrastructure focussing capacity and fleet efficiency.

· You will produce high quality software that is unit tested, code reviewed, and checked in

regularly for continuous integration.

· You will provide technical leadership, driving and performing best engineering practices to

initiate, plan, and execute large-scale, cross functional, and company-wide critical programs. · Identify, leverage, and successfully evangelize opportunities to improve engineering

productivity.

Basic Qualifications

· BS (or higher, e.g., MS, or PhD) in Computer Science or related technical field involving

coding (e.g., physics or mathematics), or equivalent technical experience.

· 2+ years of industry experience.

· Must have 2+ years of experience in managing and scaling Kubernetes infrastructure.

· Experience programming language Golang or Java.

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 building and running distributed large-scale systems in production (24x7).

· Experience with Kubernetes controller development, automating cluster management

· Golang coding experience

· Experience with Distributed Storage/Databases and/or analytics technologies (e.g., Pinot,

Druid, Redshift, Hadoop, Spark, Presto, Kafka, Flink, etc., or similar) is highly valued.

Suggested Skills:

· API Development

· Kubernetes Infrastructure

· Distributed Large-Scale Systems in Production

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 $117,000 - $192,000. Actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations.

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

Equal Opportunity Statement

LinkedIn is committed to diversity in its workforce and is 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 an Affirmative Action and Equal Opportunity Employer as described in our equal opportunity statement here: https://microsoft.sharepoint.com/:b:/t/LinkedInGCI/EeE8sk7CTIdFmEp9ONzFOTEBM62TPrWLMHs4J1C_QxVTbg?e=5hfhpE. Please reference https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf and https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf for more information.

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 accommodations@linkedin.com 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.

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

This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://lnkd.in/GlobalDataPrivacyNotice

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