Software Engineer - Compute InfrastructureAt LinkedIn

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.LinkedIn operates one of the largest privately managed compute infrastructures in the world outside the public cloud providers. As a Staff Software Engineer on the Compute Infrastructure team, you will help build and evolve the platform that powers LinkedIn at every layer - the real-time services behind products serving over a billion members, large-scale data and analytics pipelines processing petabytes daily, and the AI/ML infrastructure driving recommendations, search relevance, and generative AI at scale.The Compute Infrastructure stack is LinkedIn’s internal private cloud, purpose-built to meet the company’s unique scaling challenges. The platform is deeply Kubernetes-centric and continuously evolving to stay at the forefront of industry trends. You will work on problems that span large-scale workload orchestration, multi-cluster operations, platform reliability and efficiency, GPU compute optimization for AI/ML, and fleet health at scale - all at a scale that few organizations in the world encounter.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 and an ever-expanding product portfolio. You will work closely with a team of talented engineers to develop and operate systems that are robust, scalable, and efficient. You will also collaborate with cross-functional teams and thrive in a fast-paced, dynamic environment.ResponsibilitiesEnable thousands of LinkedIn engineering teams to deploy and operate reliably - driving impact across areas such as CI/CD pipelines that deliver a seamless developer experience, a workload platform that provides resilient orchestration at scale, a self-healing host management system with intelligent health detection and automated remediation, Kubernetes cluster lifecycle and infrastructure, and GPU compute infrastructure powering AI/ML workloads, all underpinned by intelligent autoscaling, resource allocation, and capacity managementAccelerate LinkedIn’s product velocity by improving platform observability, deployment safety, and release throughputShape technical direction across team boundaries, ensuring the platform evolves ahead of demand from new products, AI workloads, and growthStrengthen the team by mentoring engineers, raising the technical bar, and fostering a, 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 and describe the specific Accommodation requested for a disability-related limitation. Fill out an Accommodation request here: https://app.smartsheet.com/b/form/b660a0327d044969abfd7a4e73d15c36Reasonable 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 youHaving interviews in an accessible locationBeing accompanied by a service dogHaving a sign language interpreter present for the interviewA 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.San Francisco Fair Chance OrdinancePursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.Pay Transparency Policy StatementAs a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.Global Data Privacy Notice and Compliance Posters for Job CandidatesPlease use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: https://www.linkedin.com/legal/candidate-portal.By clicking the link above or any third-party link within this posting, you are leaving this site and going to a third-party website where the third-party website’s terms and privacy policy applyI’m interested Privacy Notice

culture of engineering excellenceResolve deep production issues that cut across Kubernetes internals, operating system behavior, and distributed system interactionsBasic QualificationsBA/BS Degree in Computer Science or related technical discipline, or equivalent practical experience4+ years of industry experience in software design, development, and algorithm-related solutions4+ years of experience programming in languages such as Go or PythonHands-on experience developing distributed systems, large-scale platforms, or backend servicesExperience with Kubernetes or similar container orchestration platformsPreferred QualificationsBS and 8+ years of relevant work experience, MS and 7+ years of relevant work experience, or PhD and 4+ years of relevant work experienceExperience architecting, building, and operating large-scale distributed systemsExperience with Kubernetes controller development and cluster lifecycle automationExperience contributing to or maintaining

open-source projectsDemonstrated ability to leverage agentic development tools and workflows to accelerate engineering productivitySuggested SkillsDistributed SystemsGolangKubernetesTechnical LeadershipYou will Benefit from our CultureWe 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 $175,000 - $287,000. 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.