slurm jobs in San Diego

Design, deploy, and operate large-scale HPC compute clusters and petabyte-class parallel file systems (Lustre, Ceph, BeeGFS, GPFS) at national and campus levels. Manage Linux system administration, cluster middleware (Slurm, PBS), storage integration, and network performance across high-speed Ethernet and InfiniBand infrastructure.…See more Develop automation scripts in Bash and Python, lead monitoring and security integration efforts, and evaluate emerging HPC technologies and vendor solutions.

Design, build, and operate high-performance scientific computing and storage infrastructure for reactor control and data acquisition systems. Responsibilities include architecting and tuning parallel filesystems (BeeGFS/ZFS) and ultra-low-latency networking (100GbE, RoCEv2), hardening segmented network security with strict firewall policies, automating bare-metal provisioning via Bash/Ansible, and managing physical data center operations including rack deployment and hardware diagnostics.…See more Requires 15+ years of Linux systems administration, deep expertise in RHEL kernel tuning, storage (ZFS/RAID/LVM), TCP/IP networking, and enterprise infrastructure.

Linux Systems Engineer II role supporting biotech/scientific computing environments. Responsible for designing, implementing, and maintaining Linux systems (Red Hat, Rocky, CentOS, Ubuntu), storage infrastructure (NFS, ZFS), HPC clusters (Slurm), virtualization, and containerized environments.…See more Requires 3–5+ years of hands-on Linux administration, scripting (BASH, Python), disaster recovery, and backup solutions; will also mentor junior IT staff and participate in cross-functional projects.

Linux Infrastructure Engineer responsible for designing, building, and maintaining ultra-high-performance data center infrastructure supporting scientific computing and operational technology systems. Core duties include architecting and tuning software-defined storage (ZFS, BeeGFS, NVMe), managing 100GbE networking with RDMA, automating bare-metal provisioning via Ansible and Bash, and ensuring OT security through segmented, firewalled network architecture.…See more Requires 15+ years of systems administration experience, expert-level Linux (RHEL) and storage knowledge, and hands-on data center operations including physical deployment, diagnostics, and hardware lifecycle management.

Senior Staff Engineer responsible for designing and building an MLOps platform that supports distributed AI training, reinforcement learning, and foundation model development at scale. You will architect Kubernetes-native infrastructure for GPU workloads, design self-service AI development workflows, manage the data and model lifecycle, and lead platform distribution across cloud, on-premises, and air-gapped environments.…See more The role requires deep expertise in modern AI frameworks (PyTorch, Hugging Face Transformers), distributed systems, GPU scheduling, and cloud-native infrastructure, with a focus on enabling researchers and engineers to move from experimentation to production rapidly.

Lead the design, development, and operation of Qualcomm's enterprise AI platform, supporting agentic AI, model lifecycle management, and multi-cloud ML/inference infrastructure. Own core platform services including identity/RBAC, secrets, service meshes, observability, vector stores, and model gateways across on-prem GPU clusters and managed cloud services.…See more Manage a ~10-engineer global team (platform, SRE, MLOps/LLMOps), drive incident response and continuous improvement, and partner with product and security teams on AI governance and high-impact use cases.

As a Datacenter AI Systems and Solutions Engineer at Qualcomm, you will research, develop, and optimize end-to-end AI/ML solutions that integrate Qualcomm's AI inference accelerators with system software and ecosystem components. You will lead the design and deployment of production-ready Generative AI and LLM applications, perform model benchmarking and performance analysis, and serve as a technical lead for customer engagements on AI model optimization and inference tuning.…See more The role requires deep expertise in AI systems architecture, MLOps practices, and large-scale distributed systems, with hands-on proficiency in Python, ML frameworks, containerization, and orchestration platforms. You will drive system-level requirements, hardware/software co-design, and influence product direction through performance analysis and optimization strategies.