Senior HPC Systems Architect
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Role details
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Job description
*Note: This position requires presence in our San Francisco or San Jose office location 4 days per week; Lambdaβs designated work from home day is currently Tuesday.
Architecture leads the design, development, and execution of next-generation GPU clusters. Our team gets first access to the latest technologies and is responsible for translating emerging platform capabilities into scalable, production-ready infrastructure. Our scope spans from rack and pod level system arrangement that maximizes the data center power footprint, to right-sizing compute fabrics that meet the most demanding customer workloads.
We work at the intersection of GPU systems, high-performance networking, power and cooling, data center design, and customer-scale AI infrastructure., * Design and architect advanced HPC systems optimized for large-scale computational workloads and AI applications.
- Collaborate with internal teams and stakeholders to define system requirements and performance goals.
- Develop comprehensive testing frameworks to rigorously assess system performance, scalability, and reliability.
- Evaluate emerging technologies and architectural approaches to continuously enhance infrastructure capabilities.
- Create detailed architectural plans, documentation, and blueprints to guide implementation teams.
- Provide technical leadership and mentoring to engineering teams, fostering best practices in HPC architecture.
Requirements
System Architecture, Cloud Computing, Artificial Intelligence (AI), Electricity, AWS Lambda, Work From Home, Network Operations Center, GPU (Graphics Processing Unit), Emerging Technology, Right-Sizing, Weβre looking for a Senior HPC Systems Architect with extensive experience designing, developing, and testing large-scale high-performance computing (HPC) infrastructures. This strategic role focuses on crafting cutting-edge liquid-cooled HPC solutions., * 8+ years of experience designing and architecting large-scale HPC and distributed computing systems.
- Expert-level knowledge of HPC hardware including GPU clusters, compute nodes, high-speed networking (InfiniBand, Ethernet), and distributed storage.
- Hands-on experience with direct-to-chip liquid cooling systems.
- Proven expertise in creating robust performance benchmarks, capacity planning, and system validation.
- Exceptional skills in system architecture, design documentation, and technical specifications.
- Ability to work collaboratively across teams, ensuring alignment of technical solutions with business objectives.
- Self-motivated, strategic thinker with strong analytical and problem-solving capabilities.
Nice to Have
- Prior experience with AI infrastructure design.
- Familiarity with cloud computing environments and hybrid cloud HPC architectures.
- Knowledge of automation and orchestration tools (Ansible, Terraform, Kubernetes).
Benefits & conditions
About Lambda
- Founded in 2012, with 500+ employees, and growing fast
- Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove
- We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
- Our values are publicly available: https://lambda.ai/careers
- We offer generous cash & equity compensation
- Health, dental, and vision coverage for you and your dependents
- Wellness and commuter stipends for select roles
- 401k Plan with 2% company match (USA employees)
- Flexible paid time off plan that we all actually use
About the company
Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambdaβs mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.
If youβd like to build the worldβs best AI cloud, join us.
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