GPU Cluster Architect

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a GPU Cluster Architect based in the United States.

This is a remote, high-impact architecture role focused on designing next-generation AI infrastructure at massive scale.

• Architect scalable GPU cluster topologies encompassing compute nodes, high-performance interconnects, storage systems, and control planes.
• Define and evaluate infrastructure architectures capable of supporting large-scale AI and machine-learning workloads across multiple data center sites.
• Model workload requirements for applications such as large language model training and inference, using latency, bandwidth, GPU density, and other performance factors to guide architectural decisions.
• Design and validate high-throughput, low-latency networking architectures at both POD and data-center scale, including InfiniBand and Ethernet-based environments.
• Work with network architecture teams to evaluate and validate technologies such as InfiniBand HDR/NDR and RoCEv2.
• Partner with storage engineering teams to optimize infrastructure for training datasets, checkpointing, and other demanding AI workloads.
• Analyze monitoring and telemetry signals to identify design issues, reliability risks, and opportunities for architectural improvement.
• Collaborate closely with site reliability, networking, storage, and data center engineering teams to operationalize, deploy, and scale infrastructure architectures.
• Contribute to automation and telemetry initiatives that improve the visibility, performance, and reliability of large-scale GPU environments.
• Make end-to-end architectural decisions that balance scalability, performance, reliability, operational complexity, and infrastructure efficiency.

• 5+ years of experience designing and architecting large-scale computing or GPU clusters.
• Deep understanding of modern GPU architectures, including NVIDIA, AMD, or comparable platforms.
• Strong experience with high-performance computing interconnects, particularly InfiniBand and RoCE.
• Solid background in systems architecture, networking, hardware infrastructure, and hardware reliability.
• Understanding of GPU cluster design principles, including compute topology, network architecture, storage integration, and control-plane considerations.
• Experience evaluating infrastructure performance and making architecture decisions based on workload characteristics such as latency, bandwidth, and compute density.
• Experience with scripting or software development for automation, telemetry, monitoring, or infrastructure tooling using languages such as Python or Go.
• Ability to analyze technical signals and operational data to identify infrastructure issues and inform design improvements.
• Strong cross-functional collaboration skills, with the ability to work effectively with networking, storage, site reliability, and data center engineering teams.
• Strong analytical and problem-solving abilities, with a practical approach to complex infrastructure challenges.
• Ability to work independently in a fast-moving environment while taking ownership of significant architectural decisions.
• Excellent communication skills and the ability to explain complex technical architectures and tradeoffs to technical stakeholders.

• Competitive compensation ranging from $184,000 to $318,000 OTE, including base salary and performance bonus.
• Equity in the form of RSUs may be available at certain salary grades.
• 100% company-paid medical, dental, and vision insurance for employees and their families.
• 401(k) plan with up to a 4% company match and immediate vesting.
• Paid parental leave: 20 weeks for primary caregivers and 12 weeks for secondary caregivers.
• Remote work reimbursement of up to $85 per month for mobile and internet expenses.
• Company-paid short-term disability, long-term disability, and life insurance.
• Remote work flexibility for U.S.-based employees.
• Career growth and ongoing learning opportunities.
• Opportunity to work on large-scale AI and machine-learning infrastructure projects.
• Collaborative, international environment with experienced engineering and AI professionals.
• High level of ownership and opportunities to contribute to technically ambitious infrastructure initiatives.
• Work environment that encourages innovation, initiative, and continuous improvement.