[All remote jobs](https://jobicy.com/jobs.md)[![Nebius logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2026/06/d90c0566-221.webp)](https://jobicy.com/company/nebius.md)[Nebius](https://jobicy.com/company/nebius.md) # GPU Cluster Architect AI Summary Nebius is seeking a GPU Cluster Architect to design large-scale AI infrastructure spanning GPU compute, high-performance networking, storage, and data-center systems. The role owns architectural decisions for clusters of tens of thousands of GPUs, with emphasis on performance, reliability, cooling, power, and operational scalability. The architect will model AI training and inference workloads and collaborate with networking, storage, SRE, and data-center engineering teams. Candidates need substantial cluster-design experience, deep familiarity with NVIDIA or AMD GPU platforms, and expertise in InfiniBand, RoCE, automation, and telemetry. This US-remote role is suited to a senior infrastructure architect who can translate demanding AI workload requirements into production-ready platform designs.[Apply for this job](#job-application)[View company](https://jobicy.com/company/nebius.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUSD 184k–318k / yrDepartment[DevOps & Infrastructure](https://jobicy.com/categories/admin.md)EmploymentFull TimeExperienceOpen levelPublished5 Nov 2026Apply before5 Dec 2026Listing views23Application actions2Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. ### The role We are seeking a GPU Cluster Architect to drive the design of our next-generation AI infrastructure. In this high-impact, hands-on role, you will make end-to-end architectural decisions across compute, networking, and storage — ensuring our platforms can meet the massive scale, performance, and reliability requirements of modern AI workloads. This is a high-impact, hands-on architecture role where you’ll define how tens of thousands of GPUs are interconnected, cooled down, powered, and optimized across multiple data center sites. You are welcome to work remotely from the USA. Your responsibilities will include: * Cluster Design: Architect scalable GPU cluster topologies including compute nodes, interconnect (InfiniBand, Ethernet), storage, and control planes. * Performance Modeling: Analyze AI/ML workloads (e.g. LLM training, inference) to inform design tradeoffs across latency, bandwidth, and GPU density. * Network Architecture: Align with network architect relevant design and validate low-latency, high-throughput interconnects (e.g., InfiniBand HDR/NDR, RoCEv2) at POD and DC scale. * Storage Integration: Work with storage teams to optimize performance for training datasets, checkpointing, and others. * Reliability & Monitoring: Understand and analyze signal from monitoring systems to the detect flows in design * Collaboration: Partner with site reliability, networking, storage, and DC engineering teams to operationalize and scale your architecture. We expect you to have: * 5+ years of experience designing clusters. * Deep understanding of modern GPU architecture (NVIDIA, AMD, etc.). * Experience with HPC interconnects (InfiniBand & RoCE). * Solid background in systems architecture, networking, and hardware reliability. * Experience in scripting for automation and telemetry pipelines (Python, Go, etc.) Key employee benefits in the US: * Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families. * 401(k) plan: Up to 4% company match with immediate vesting. * Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. * Remote work reimbursement: Up to $85/month for mobile and internet. * Disability & life insurance: Company-paid short-term, long-term and life insurance coverage. Compensation We offer competitive salaries ranging from $184K to $318K OTE, which includes base salary and performance bonus. Equity in the form of RSUs may be available at certain salary grades. What we offer * Competitive salary and comprehensive benefits package. * Opportunities for professional growth within Nebius. * Hybrid working arrangements. * A dynamic and collaborative work environment that values initiative and innovation. We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us! Benefits & Perks: * Competitive compensation * Career growth and learning opportunities * Flexibility and ownership * Collaborative and innovative culture * Opportunity to work on impactful AI projects * International environment and talented teams What’s it like to work at Nebius: Fast moving – Bold thinking – Constant growth – Meaningful impact – Trust and real ownership – Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know. Show more [Apply now >](https://jobicy.com/jobs/159082-gpu-cluster-architect.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThe position requires end-to-end technical ownership of highly complex GPU clusters at exceptional scale, combining hardware, networking, storage, and reliability engineering. Architectural choices directly affect AI workload performance, data-center operations, and platform scalability. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Highly competitive$251,000US market range (per year)$190k–$280k0$308k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses $184,000–$318,000 USD OTE, including base salary and a performance bonus. The yearly cadence is inferred from the compensation scale and senior US full-time role. The displayed midpoint is $251,000 yearly OTE; the estimated US market base-pay range for a comparable GPU infrastructure architect is $190,000–$280,000 per year. ## Core skills Skills and capabilities most closely associated with this opportunity. [GPU cluster architecture](https://jobicy.com/jobs?search_keywords=GPU%20cluster%20architecture.md)[High-performance computing](https://jobicy.com/jobs?search_keywords=High-performance%20computing.md)[NVIDIA GPU architecture](https://jobicy.com/jobs?search_keywords=NVIDIA%20GPU%20architecture.md)[AMD GPU architecture](https://jobicy.com/jobs?search_keywords=AMD%20GPU%20architecture.md)[InfiniBand](https://jobicy.com/jobs?search_keywords=InfiniBand.md)[RoCEv2](https://jobicy.com/jobs?search_keywords=RoCEv2.md)[Ethernet networking](https://jobicy.com/jobs?search_keywords=Ethernet%20networking.md)[Storage architecture](https://jobicy.com/jobs?search_keywords=Storage%20architecture.md)[AI workload performance modeling](https://jobicy.com/jobs?search_keywords=AI%20workload%20performance%20modeling.md)[LLM training infrastructure](https://jobicy.com/jobs?search_keywords=LLM%20training%20infrastructure.md)[Data center infrastructure](https://jobicy.com/jobs?search_keywords=Data%20center%20infrastructure.md)[Hardware reliability](https://jobicy.com/jobs?search_keywords=Hardware%20reliability.md)[Python automation](https://jobicy.com/jobs?search_keywords=Python%20automation.md)[Go programming](https://jobicy.com/jobs?search_keywords=Go%20programming.md)[Telemetry pipelines](https://jobicy.com/jobs?search_keywords=Telemetry%20pipelines.md) Sample interview questionsHow would you design a GPU cluster topology for large-scale distributed LLM training?I would begin with workload characteristics such as model size, training parallelism, communication patterns, storage throughput, and availability targets. I would then define a modular pod architecture with balanced GPU density, non-blocking or appropriately oversubscribed InfiniBand or RoCE fabrics, high-throughput storage, and clear scaling boundaries. Finally, I would validate the design through simulation, benchmark representative workloads, and incorporate observability and failure-domain requirements from the outset. What trade-offs do you consider when choosing InfiniBand versus RoCEv2? I assess latency and bandwidth needs, GPU collective communication behavior, operational maturity, existing network standards, cost, and the team’s ability to manage lossless Ethernet requirements. InfiniBand is often compelling for predictable HPC performance and mature GPU workload tooling, while RoCEv2 can integrate effectively into Ethernet-based environments when congestion control, PFC, ECN, and telemetry are engineered carefully. The choice should be validated against real workload benchmarks and operational risk. How would you identify and resolve a performance bottleneck in a distributed training cluster? I would correlate application-level metrics, collective communication telemetry, GPU utilization, CPU and PCIe activity, fabric counters, and storage latency. This helps separate bottlenecks caused by data loading, network congestion, topology imbalance, stragglers, insufficient storage throughput, or software configuration. I would test a focused hypothesis, compare results against a known baseline, and deploy the remediation with monitoring to confirm sustained improvement. How do you design for reliability across multiple GPU data-center sites? I define failure domains at the node, rack, pod, fabric, storage, and site levels, then ensure the scheduler and control planes can tolerate failures within those boundaries. I include redundant network paths, capacity headroom, hardware health monitoring, automated remediation, and well-tested recovery procedures. For multi-site designs, I also clarify which workloads require local high-performance communication and which can safely use asynchronous replication or federated control. Describe how you would use automation and telemetry in operating GPU infrastructure. I would automate repeatable lifecycle tasks such as provisioning, configuration validation, firmware compliance, health checks, and capacity inventory using version-controlled workflows. Telemetry should cover GPU, network, storage, power, cooling, and workload-level signals with actionable alert thresholds and dashboards. The goal is to detect degradation early, shorten incident resolution, and provide data that feeds future architectural decisions. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. 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