26 to 35 of 35 Slurm Workload Manager Jobs in the UK

approach: you like working with the people who use the systems Bonus points for: parallel or high-availability storage (Lustre, Ceph, Weka, PEAK:AIO), Slurm or LSF, and Python scripting. Why it’s worth a look Access to the latest AI tooling, and encouragement … approach: you like working with the people who use the systems Bonus points for: parallel or high-availability storage (Lustre, Ceph, Weka, PEAK:AIO), Slurm or LSF, and Python scripting. Why it’s worth a look Access to the latest AI tooling, and encouragement ...

land service-led AI solutions. Lead integration of compute, storage, networking, the AI software stack (CUDA, ROCm, Triton, NIM, NVIDIA AI Enterprise, Run:ai, Slurm, Kubernetes/Kubeflow) and managed-service operating models across multiple domains, delivery units and geographies. Build business cases, TCO and unit-economics models (cost … tree topologies. Working knowledge of the AI software and orchestration stack: CUDA, cuDNN, NCCL, ROCm, Triton Inference Server, NIM, vLLM, TensorRT-LLM, Slurm, Kubernetes (with GPU Operator), Kubeflow, Run:ai, MLflow and NVIDIA AI Enterprise. Familiarity with datacenter facilities engineering for AI workloads: high-density power, liquid cooling ...

Linux system administration. Familiarity with at least one scripting language (e.g., Bash, Python). Interest in high-performance computing and willingness to learn Slurm, xCAT, and Ansible. Strong problem-solving skills and attention to detail. Good communication and collaboration skills. Ability to work independently with mentorship and as part … week. No hybrid/remote working option. Internship or academic experience in a research computing or HPC environment. Exposure to job schedulers (e.g., Slurm, LSF). Familiarity with version control systems (e.g., Git). Coursework or projects involving distributed systems, networking, or parallel computing. Understanding of basic cybersecurity concepts. ...

file systems, object storage and tiered storage solutionsEstablish technical standards, reference architectures and engineering best practices for HPC environmentsLead performance benchmarking, capacity planning and workload modelling to ensure infrastructure delivers the required throughput, latency and scalabilityIdentify architectural bottlenecks and define technical improvements to optimise overall HPC performanceProvide technical leadership … speed EthernetExperience designing storage solutions using technologies such as parallel file systems, object storage and tiered storageUnderstanding of performance engineering including benchmarking, capacity planning, workload modelling and architectural bottleneck analysisKnowledge of HPC workload scheduling and orchestration, particularly SLURM and Kubernetes-based environmentsFamiliarity with HPC software stacks including ...

parallel file systems, object storage, and tiered storage Provide technical leadership and oversight to engineering and operations teams Lead performance benchmarking, capacity planning, and workload modelling activities Identify and resolve system bottlenecks to ensure optimal throughput and scalability Establish standards, reference architectures, and best practices across HPC environments Collaborate … with internal stakeholders and external vendors to align infrastructure with evolving business needs Support the development of workload orchestration strategies using tools such as SLURM and Kubernetes The ideal candidate would have: Strong background in high-performance computing environments and infrastructure design Experience working with open-source technologies ...

controllers — so it stays responsive as object counts and node counts grow by orders of magnitude. And we build the core cluster services every workload depends on, like service discovery, so they hold up under the same pressure. We make sure the control plane is fast, correct, and always … Anthropic's accelerator fleets, including custom scheduling plugins and policies for gang scheduling, topology awareness, and preemptionScale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits, and find the next bottleneck before it finds usDesign, build, and operate core cluster services such ...

Engineer to develop and optimise GPU-accelerated software for data centre systems: low-level performance engineering for large-scale compute clusters, tying GPU workload behaviour to energy availability and grid demand. This puts CUDA/GPU performance engineering at the centre of how Fuse scales its compute infrastructure. ResponsibilitiesDesign … multi-node scaling using NCCL, MPI, or similar communication librariesWork with data center infrastructure teams on power capping, dynamic voltage/frequency scaling, and workload scheduling strategies that reduce energy cost and carbon intensityCollaborate with ML/systems engineers to integrate custom kernels into training/inference pipelinesBenchmark against ...

ADVANCE YOUR CAREER. ADVANCE THE WORLD. At AMD, we believe technology has the power to solve the world's most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people ...

training and inference workloads (LLMs, multimodal and scientific AI) across distributed clusters for cost, throughput and latency targetsLead HPC cluster design and orchestration using Slurm, Kubernetes and parallel processing models (MPI)Enhance GPU utilisation by addressing bottlenecks across compute, memory and data pipelines; collaborate with energy teams on power … infrastructure, accelerated computing or distributed systems architectureDeep knowledge of GPU architectures, AI workloads, networking and large-scale cluster operationsHands-on expertise with Slurm, Kubernetes and performance optimisation across multi-node environmentsProven ability to advise senior stakeholders and influence technical strategy at C-levelDemonstrated experience in pre-sales solutioning ...

operation of high performance storage services, supporting both internal workloads and external collaboration. The environment includes large scale HPC clusters, Linux based systems, workload schedulers such as Slurm, networking with Infiniband and parallel file systems such as GPFS. Experience with high performance storage at petabyte scale is particularly ...