Senior HPC Cluster Engineer – AI, ML

🕒 Agosto 6

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NVIDIA

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 1993

🏥 Saúde

🏭 Manufatura

🤖 Inteligência Artificial

Healthcare • Manufacturing • Artificial Intelligence

A NVIDIA é uma empresa de tecnologia líder, especializada em computação acelerada e inteligência artificial. A companhia é pioneira em avanços em unidades de processamento gráfico (GPUs), computação em nuvem, data centers e realidade virtual, com foco nos setores de games, automotivo, saúde e robótica. As inovações da empresa, como o NVIDIA Omniverse, transformam processos digitais tradicionais ao viabilizar simulações de alta fidelidade e tarefas de renderização. Suas aplicações abrangem diversos setores, desde veículos autônomos com o NVIDIA DRIVE até soluções de saúde com o NVIDIA Clara, além de análises e fluxos de trabalho impulsionados por IA.

Descrição

• Provide leadership in systems administration and service delivery on the AI/HPC fleet by coordinating system upgrades, responding to incidents, and delivering reliability improvements • Collaborate with global teams to deliver a world-class user experience in AI and HPC research • Own day-to-day operations of production AI/HPC clusters, ensuring system health, user satisfaction, and efficient resource utilization • Develop and improve the ecosystem around GPU-accelerated computing, including scalable automation solutions • Build and maintain heterogeneous AI/ML clusters on-premises and in the cloud • Create and cultivate customer and cross-team relationships to meet evolving user needs • Support researchers running workloads, including performance analysis and optimization • Analyze and optimize cluster efficiency, job fragmentation, and GPU waste to meet internal SLA targets • Conduct root cause analysis and suggest corrective actions • Proactively find and fix issues before they occur • Lead SEV triage and postmortems for reliability incidents affecting users or infrastructure • Participate in on-call rotation and incident response for critical production GPU clusters

🎯 Requisitos

• Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience • Minimum 5 years of experience designing and operating large-scale compute infrastructure • Experience with AI/HPC advanced job schedulers such as Slurm, K8s, PBS, RTDA, BCM, or LSF • Proficient in administering CentOS/RHEL and/or Ubuntu Linux distributions • Solid understanding of cluster configuration management tools including BCM, Terraform, Ansible, Puppet, and Salt • Knowledge of container technologies including Docker, Singularity, Podman, Shifter, and Charliecloud • Python programming and Bash scripting • Applied experience with AI/HPC workflows using MPI • Experience analyzing and tuning performance for varied AI/HPC workloads • Passion for continual learning and staying ahead of emerging HPC and AI/ML infrastructure technologies and approaches • Background with NVIDIA GPUs, CUDA programming, NCCL, and MLPerf benchmarking • Experience with AI/ML concepts, algorithms, models, and frameworks such as PyTorch and TensorFlow • Experience with InfiniBand, IPoIB, and RDMA • Understanding of fast, distributed storage systems such as Lustre and GPFS for AI/HPC workloads