Description
We are looking for a Senior HPC and AI Cluster Administrator to join our Networking clusters solutions HPC/AI Infrastructure team. As a key player in the most exciting computing hardware and software, you will contribute to the latest breakthroughs in artificial intelligence and GPU computing.
You will work with the latest Accelerated computing and Deep Learning software and hardware platforms, and with many scientific researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms.
Your responsibilities will include:
Deploying, managing and maintaining large scale HPC/AI clusters Managing Linux job/workload schedules and orchestration tools Supporting and maintaining continuous integration and delivery pipelines Troubleshooting and fixing, bottom up from bare metal, operating system, software stack and application level Supporting Research & Development activities and engaging in POCs/POVs for future improvements
To succeed in this role, you will need:
Bachelor's Degree in Computer Science, Engineering, or a related field; or equivalent experience 5+ years of experience Knowledge of HPC and AI solution technologies from CPU's and GPU's to high speed interconnects and supporting software Experience with job scheduling workloads and orchestration tools such as Slurm, K8s Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu) networking (sockets, firewalls, iptables, wireshark, etc.) and internals, ACLs and OS level security protection and common protocols e.g. TCP, DHCP, DNS, etc. Experience with multiple storage solutions such as Lustre, GPFS, zfs and xfs. Familiarity with newer and emerging storage technologies. Python programming and bash scripting experience, automation and configuration management tools such as Jenkins, Ansible, Gitops Knowledge of Networking Protocols like InfiniBand, Ethernet Experience with virtual systems (for example VMware, Hyper-V, KVM) Familiarity with cloud computing platforms (e.g. AWS, Azure, Google Cloud)
If you have knowledge of CPU and/or GPU architecture, Kubernetes, container related microservice technologies, experience with GPU-focused hardware/software (DGX, Cuda), or background with RDMA (InfiniBand or RoCE) fabrics, you will stand out from the crowd.