Staff Engineer, Hardware Reliability

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.

This role will be based in Sunnyvale CA.

We are looking for a highly skilled self-motivated Staff Engineer to join our Hardware Capacity Engineering (HCE) team and help us scale and sustain the infrastructure that powers LinkedIn. HCE qualifies integrates and operates the full range of hardware in our on-prem data centers such as general-purpose compute GPU/accelerator storage and networking platforms across a large-scale multi-vendor multi-generation fleet. This role spans both bringing new platforms into production and keeping our existing fleet healthy performant and reliable backed by the software firmware automation and fleet-health systems the team builds.

In this role you will identify requirements and the best-suited hardware platform or solution integrate that solution into our on-prem data center environment and help operate and continuously improve the existing fleet at scale. You will build software and automation that make the fleet observable performant and reliable and partner closely with SRE software engineering AI/ML and hardware vendors.

Responsibilities

• Collaborate with LinkedIn engineering teams to collect requirements for LinkedIn applications and provide guidance on selecting the best-suited hardware platforms and solutions across general-purpose compute GPU/accelerator storage and networking.
• Design test environments and testing scenarios; benchmark compute storage and power (e.g. SPEC SPECpower etc) and provide detailed analysis of qualification and performance results for varied audiences including engineers and senior leadership.
• Qualify and integrate new server platforms and components end-to-end working with hardware vendors on optimal configurations and driving the full integration process.
• Work jointly with other teams on cost and TCO analysis for proposed solutions present them to decision makers and define SLAs and technical standards with partner teams.
• Qualify BIOS BMC and component firmware. Drive fleet-wide upgrade programs.
• Support and improve the reliability of our existing large-scale diverse fleet including fault detection and remediation firmware management and OS and security compliance.
• Design build (AI-assisted) and own automation for hardware qualification provisioning lifecycle and fleet health monitoring and telemetry analysis.
• Contribute to AI/ML infrastructure performance and reliability of GPU platforms InfiniBand/RDMA  as part of the teams broader scope.
• Troubleshoot complex hardware firmware kernel and platform issues across the fleet and lead critical production incident response.

Qualifications :

Basic Qualifications

• BS in Computer Science Computer Engineering or a related technical field or equivalent practical experience.
• 6 years of experience working in Linux-based infrastructure systems or hardware engineering.
• 4 years of experience with hardware troubleshooting systems engineering and performance analysis.
• Experience developing software or automation (AI-assisted or otherwise) for infrastructure at scale.

Preferred Qualifications

• Experience with x86 server architecture and multi-vendor hardware BMC/BIOS and firmware (IPMI/Redfish).
• Experience qualifying and integrating new hardware platforms and operating them across a large-scale diverse multi-generation fleet.
• Experience with hardware provisioning imaging/OS and lifecycle or inventory systems
• Experience building fleet health observability or reliability tooling (fault detection SMART and telemetry analysis data-driven thresholds).
• Experience benchmarking with common tools such as SPEC SPECpower fio unixbench and similar.
• Experience with storage devices and performance engineering (NVMe/SSD/HDD) and/or distributed/parallel filesystems (GPFS HDFS).
• Experience with GPU/accelerator platforms and the ML training stack (NCCL/collective communications CUDA) and high-performance networking (InfiniBand/RDMA RoCE).
• Experience with Kubernetes and containerized workloads.
• Experience working with hardware vendors on both designing a solution and troubleshooting issues.
• Demonstrated experience putting together summary reports and visual presentations of the results of benchmarks and performance tests for technical and executive audiences.
• Familiarity with HPC/Machine Learning environments and solutions.

Suggested Skills

• Linux
• Hardware Qualification & Integration
• Firmware / BMC (BIOS IPMI/Redfish)
• Fleet Reliability & Observability
• Linux Performance (Compute Storage IO)
• GPU / AI Infrastructure

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 $156000 to $255000. 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 Information :

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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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No

Employment Type :

Full-time