Staff Software Engineer - Compute Infrastructure
About The Position
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.
Requirements
- BA/BS Degree in Computer Science or related technical discipline, or equivalent practical experience
- 4+ years of industry experience in software design, development, and algorithm-related solutions
- 4+ years of experience programming in languages such as Go or Python
- Hands-on experience developing distributed systems, large-scale platforms, or backend services
- Experience with Kubernetes or similar container orchestration platforms
Nice To Haves
- BS and 8+ years of relevant work experience, MS and 7+ years of relevant work experience, or PhD and 4+ years of relevant work experience
- Experience architecting, building, and operating large-scale distributed systems
- Experience with Kubernetes controller development and cluster lifecycle automation
- Experience contributing to or maintaining open-source projects
- Demonstrated ability to leverage agentic development tools and workflows to accelerate engineering productivity
Responsibilities
- Enable 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 management
- Accelerate LinkedIn's product velocity by improving platform observability, deployment safety, and release throughput
- Shape technical direction across team boundaries, ensuring the platform evolves ahead of demand from new products, AI workloads, and growth
- Strengthen the team by mentoring engineers, raising the technical bar, and fostering a culture of engineering excellence
- Resolve deep production issues that cut across Kubernetes internals, operating system behavior, and distributed system interactions
Benefits
- Generous health and wellness programs
- Time away for employees of all levels
- Annual performance bonus
- Stock
- Other applicable incentive compensation plans
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Associate degree
