HPC Specialist Solutions Architect

Why work at Nebius Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field. Where we work Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with RD hubs across Europe, North America, and Israel. The team of over 800 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI RD team. Customer experience: Customer experience at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community. The role We are seeking a Specialist HPC Infrastructure Solutions Architect to design, build, and optimize next-generation high-performance computing (HPC) platforms for AI, simulation, and large-scale data processing workloads. The ideal candidate combines deep knowledge of cloud-native architecture, Kubernetes orchestration, networking, and HPC system design with hands-on experience implementing NVIDIA GPU-based compute environments and MLOps toolchains. This role sits at the intersection of infrastructure engineering, accelerated computing, and AI systems design, shaping the foundation for high-throughput, low-latency distributed workloads in cloud environment. You’re welcome to work remotely from the United States or Canada. Your responsibilities will include: Architect and implement scalable HPC clusters optimized for AI, simulation, and distributed training, leveraging container orchestration frameworks and schedulers (e.g., Kubernetes, Slurm). Design and integrate GPU-accelerated compute infrastructures featuring NVIDIA Hopper, Blackwell architectures, NVLink/NVSwitch, and InfiniBand/RoCE Interconnects. Deploy, and manage GPU Operator and Network Operator stacks for automated lifecycle management of GPU and high-speed networking components. Design and validate cloud HPC environments, focusing on low-latency, high-bandwidth networking, multi-GPU scaling, and efficient workload scheduling. Lead reference architectures for AI/ML model training, data pipelines, and MLOps integrations using modern observability and CI/CD tooling. Collaborate with hardware vendors (e.g., NVIDIA) and cloud providers to evaluate and optimize emerging HPC and GPU technologies. Benchmark system performance, identify bottlenecks, and tune resource utilization across compute, network, and storage tiers. Provide expert-level technical guidance to customers, internal teams, and partners on HPC architecture patterns, operational excellence reviews and customer engagements We expect you to have: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (Ph.D. a plus) 3+ years of hands-on experience architecting HPC or large-scale GPU clusters. Expertise in Linux systems, Kubernetes, container runtimes (containers, CRI-O, Docker), and related CI/CD practices. Strong understanding of HPC networking protocols and RDMA stacks (InfiniBand, NVLink/NVSwitch) Deep understanding of storage and I/O optimization for large datasets (Ceph, L ... (truncated, view full listing at source)