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 lead their ML infrastructure initiatives. This role represents a unique opportunity to shape the future of AI/ML infrastructure at scale.
The position focuses on designing and maintaining large-scale GPU infrastructure for machine learning and AI workloads. As the technical leader, you'll be responsible for crucial decisions regarding hardware selection, networking architecture, and storage solutions that power LinkedIn's AI initiatives.
Key aspects of the role include:
- Architecting high-performance GPU infrastructure, including server SKU selection and memory configurations
- Designing sophisticated networking solutions for distributed training
- Leading operational support and maintaining observability systems
- Collaborating with data scientists and ML engineers to optimize infrastructure
The ideal candidate brings 8+ years of experience in distributed systems, with at least 3 years focused on GPU-based ML workloads. Strong knowledge of high-performance networking, containerization, and modern MLOps practices is essential.
LinkedIn offers a competitive compensation package ($149,000 - $247,000) and emphasizes a hybrid work environment that balances remote flexibility with in-office collaboration at their Sunnyvale campus. The company's commitment to professional growth, coupled with its mission to create economic opportunity for the global workforce, makes this an exciting opportunity for a senior technologist looking to make a significant impact.
The role combines technical leadership with strategic thinking, requiring someone who can both architect complex systems and influence long-term technical direction. You'll work at the intersection of infrastructure and ML, helping to scale LinkedIn's AI capabilities while ensuring reliability and performance.
This position offers the chance to work with cutting-edge AI technologies while solving unique challenges of operating at LinkedIn's scale. The company's culture emphasizes trust, inclusion, and professional development, making it an ideal environment for continued growth and impact.
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
- Lead end-to-end operational support for production GPU fleets
- Develop and maintain observability tooling
- Partner with Data Scientists, ML Engineers, and DevOps teams
- Influence the 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 (InfiniBand, RoCE, or high-speed Ethernet)
- Experience with containerization (Docker, Singularity) and job schedulers
- Excellent communication skills
- Strong organizational skills
Benefits For Sr Staff Engineer, ML Infrastructure and Performance
- Flexible Work
- Professional Development
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