Sr Staff Engineer, ML Infrastructure and Performance
Description For Sr Staff Engineer, ML Infrastructure and Performance
LinkedIn, the world's largest professional network, is seeking a Senior Staff Engineer to spearhead their ML Infrastructure and Performance initiatives. This is a unique opportunity to shape the future of AI/ML infrastructure at massive scale.
The role combines deep technical expertise in GPU infrastructure, networking, and storage with strategic leadership. You'll be responsible for architecting and maintaining the foundation that powers LinkedIn's cutting-edge AI initiatives. This includes selecting optimal hardware configurations, designing high-performance networking solutions, and ensuring reliable, efficient operations of large-scale GPU clusters.
As a technical leader, you'll collaborate across teams - from data scientists to infrastructure engineers - ensuring LinkedIn's ML platform meets both performance and cost goals. You'll guide junior engineers, establish best practices, and influence the long-term technical roadmap. The role requires expertise in GPU computing, high-performance networking (InfiniBand, RoCE), parallel storage systems, and modern observability tools.
This hybrid position offers the flexibility to work both remotely and from LinkedIn's Sunnyvale campus. You'll be part of a company culture built on trust, care, inclusion, and fun, with a mission to create economic opportunity for every member of the global workforce. The compensation package includes a competitive salary range of $149,000 to $247,000, plus potential for annual performance bonus and stock options.
The ideal candidate brings 8+ years of experience with distributed systems, including 3+ years focused on GPU-based ML workloads. Beyond technical skills, you should excel at communication, organization, and cross-functional collaboration. If you're passionate about solving complex infrastructure challenges and want to impact how the world's largest professional network leverages AI, this role offers an exceptional opportunity to lead and innovate.
Responsibilities For Sr Staff Engineer, ML Infrastructure and Performance
- Design, build, and maintain large-scale GPU infrastructure for ML and AI workloads
- Define and evaluate GPU server SKUs, memory configurations, and CPU-GPU ratios
- Design high-throughput, low-latency networking solutions
- Assess and integrate scalable storage solutions
- Lead end-to-end operational support for production GPU fleets
- Develop and maintain observability tooling
- Establish SLAs, SLOs, and best practices
- Partner with Data Scientists and ML Engineers
- Guide junior engineers in architecture best practices
- Influence long-term roadmap for ML/AI infrastructure
Requirements For Sr Staff Engineer, ML Infrastructure and Performance
- Bachelor's degree in Computer Science, Electrical Engineering, or related field or equivalent industry experience
- 8+ years of experience designing and managing large-scale, distributed systems or HPC environments
- 3+ years focused on GPU-based ML or AI workloads
- Deep knowledge of high-performance networking and parallel storage systems
- Experience with containerization and job schedulers
- Excellent communication skills
- Strong organizational skills
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