PpNVIDIA is looking for an experienced HPC DevOps and Network Engineer to help build the supercomputers and HPC clusters of the future. As a Senior HPC DevOps Engineer, you will drive breakthroughs in artificial intelligence and GPU computing, working with accelerated computing and deep learning platforms to craft improved workflows and develop leading solutions for scientific researchers, developers, and customers. /p h3What You’ll Be Doing /h3 ul liDesign, implement, and maintain large‑scale HPC/AI clusters with state‑of‑the‑art monitoring, logging, and alerting systems. /li liUtilize and develop tools to manage infrastructure as code, ensuring scalable and repeatable deployments. /li liDevelop and maintain CI/CD pipelines to automate deployment processes. /li liBuild automation scripts and tools for deployment, configuration management, and operational monitoring. /li liDevelop complex networking automations. /li liPerform comprehensive troubleshooting from bare metal to application level to ensure system reliability and efficiency. /li liServe as a technical resource and share best practices with internal teams. /li liSupport RD activities and engage in POCs and POVs for future improvements. /li /ul h3What We Need To See /h3 ul liB.Sc. in Computer Science, Engineering, or related field with 5+ years of experience. /li liDeep knowledge of HPC and AI solution technologies, including CPUs, GPUs, high‑speed interconnects, and supporting software. /li liAdvanced proficiency in programming and scripting languages with solid object‑oriented programming principles. /li liFamiliarity with Jenkins, Ansible, Puppet/Chef. /li liExcellent knowledge of Windows and Linux (RedHat/CentOS, Ubuntu), networking and OS‑level security. /li liDeep understanding of networking protocols such as InfiniBand and Ethernet. /li liExperience with job scheduling workloads and orchestration tools such as Slurm and Kubernetes. /li liBackground with multiple storage solutions like Lustre, GPFS, ZFS, and XFS. /li liExpertise with virtual systems (VMware, Hyper‑V, KVM, Citrix). /li liFamiliarity with cloud platforms (AWS, Azure, Google Cloud). /li /ul h3Ways To Stand Out From The Crowd /h3 ul liProven networking experience or strong knowledge through professional training. /li liKnowledge of CPU and/or GPU architecture. /li liUnderstanding of Kubernetes and container‑related microservices. /li liExperience with GPU‑focused hardware/software (DGX, CUDA). /li liBackground with RDMA (InfiniBand or RoCE) fabrics. /li /ul pAt NVIDIA, we value diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We provide reasonable accommodations to ensure all individuals can participate in the job application or interview process, perform essential job functions, and receive other benefits and privileges of employment. Join us and be part of a team that's pushing the boundaries of technology and making a real impact in the world. /p pJob ID: JR /p pLocation: Madrid, Community of Madrid, Spain /p h3Seniority level /h3 ul liMid‑Senior level /li /ul h3Employment type /h3 ul liFull‑time /li /ul h3Job function /h3 ul liEngineering and Information Technology /li /ul h3Industries /h3 ul liComputer Hardware Manufacturing, Software Development, and Computers and Electronics Manufacturing /li /ul pReferrals increase your chances of interviewing at NVIDIA by 2x. /p /p #J-18808-Ljbffr