13 of 13 Slurm Workload Manager Jobs in London

details. Nice to Have Experience managing physical data centres, co‐location facilities, or hybrid infrastructure environments. Working knowledge of ML orchestration frameworks (e.g., Ray, Slurm, Kubeflow). Background in media pipelines, VFX tooling, or media compliance standards (MPA, ISO 27001). Prior experience working in a hybrid startup/ ...

continuous, declarative platform delivery. Pipeline orchestration: Kubeflow Pipelines, Apache Airflow, or Argo Workflows to orchestrate multi-stage training, fine-tuning, and inference pipelines. Cluster & workload scheduling: Slurm, Run:ai, and NVIDIA Base Command Manager for GPU job scheduling; Kubernetes-native GPU scheduling including device plugins ...

technical direction of the company from day one. What we’re looking for Large‐scale distributed training. PyTorch and modern deep‐learning frameworks. Kubernetes, Slurm or GPU orchestration platforms. AWS and specialist GPU cloud providers. High‐performance computing and distributed systems. Training optimisation, memory management and networking. MLOps tooling ...

more of the following programming languages: C++, Python, Cuda, or Bash. Experience in architecting an HPC platform with scheduling middleware (e.g., Slurm, Torque, Symphony or GridServer) and in deployment, tuning and management of HPC technologies in a multi‐user environment. High level understanding of the underlying infrastructure platform ...

Claude Code, Codex, Kimi Code, Pi Agent, Droid, or similar agentic coding systems as a development surface Experience with GPU clusters on Kubernetes, Slurm, Ray, custom schedulers, or cloud GPU orchestration NCCL, UCX, NVSHMEM, RDMA, InfiniBand, RoCE, or EFA Rust, C++, CUDA, Go, or systems‐level performance work ...

Background in numerical computing, HPC, or distributed systems, including familiarity with GPUs/TPUs, high-performance networking (NVLink/InfiniBand), Kubernetes/Slurm, and OS internals Expertise in Python and deep experience with modern deep learning frameworks (PyTorch and/or JAX) Advanced degree (MS or PhD) in Computer ...

engineer who thrives in early stage startup environments and prefers broad systems ownership over narrow specialisation. Technical Expertise: Strong production background with AWS, Kubernetes, Slurm, PyTorch, and distributed training frameworks. Deep hands‐on experience with GPU compute optimisation, cluster scheduling, and high performance networking is essential. Relevant Background: Experience ...

+ years working on large‐scale ML codebases. Hands‐on with PyTorch, JAX or TensorFlow; comfortable with distributed training (DeepSpeed/FSDP/SLURM/K8s). Experience in deep learning, NLP or LLMs; bonus for CUDA or data‐pipeline chops. Strong software‐design instincts: testing, code review ...

multi-tenant serving or SLA-driven infrastructure. Background at a hyperscaler, frontier AI lab, or large-scale distributed inference system. Familiarity with Kubernetes/Slurm for cluster orchestration. Interest or experience in energy markets, grid systems, or sustainability-focused compute. Benefits Competitive salary and an equity sign-on bonus. ...

large-scale distributed systems. Research experience involving computational workloads. Experience with parallel programming (MPI, OpenMP, CUDA). Knowledge of scheduling systems such as Slurm, PBS or LSF. Contributions to technical projects, open source or research communities. Experience working with advanced computing environments. Academic Focus We are particularly interested … Parallel Programming, MPI, OpenMP, Multithreading, Concurrency, Algorithms, Data Structures, Systems Design, Kernel Development, Networking, Storage Systems, Distributed Storage, Automation, Infrastructure Automation, Shell Scripting, Bash, Slurm, PBS, LSF, Workload Scheduling, Resource Management, Linux Administration, Server Infrastructure, Cloud Infrastructure, AWS HPC, Azure HPC, Data Processing, Machine Learning Infrastructure, AI Infrastructure ...

winning them requires more than a great sales team. The Solutions Architect sits at the intersection of sales, infrastructure, and the customer, translating complex workload requirements into technically sound, commercially viable solutions on the Hyperstack platform. You’ll be the primary technical authority through the sales cycle: engaging directly … proposal, and delivery handover — acting as the primary technical authority for GPU cloud solution design. Engage directly with prospective and existing customers to understand workload requirements, technical constraints, and commercial objectives, producing detailed solution designs including architecture diagrams, network topology, storage configurations, and GPU resource allocation models. Collaborate closely ...

model lifecycle management is highly desirable Bonus/Good to Have HPC & Cluster Management: Experience handling large‐scale HPC clusters using Kubernetes and Slurm for job scheduling, resource allocation, and workload orchestration Data Engineering: Expertise with data pipelines, ETL systems, and large‐scale data processing frameworks Systems-Level ...

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 … accelerator fleets, including custom scheduling plugins and policies for gang scheduling, topology awareness, and preemption Scale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits, and find the next bottleneck before it finds us Design, build, and operate core cluster services such ...