Sr. HPC Systems Engineer (IT@JH Research Computing)

Specific Duties & Responsibilities

• Support and administer production systems used by researchers and Research Centers.
• Provide technical leadership/project management for system configuration, implementation, management, and user support for both new and existing systems.
• Research and recommend new functionality for HPC management and administration tools by exploring system-wide impacts, working with functional users to define current and future processes.
• Expertise with architecting, operating, and debugging large scale HPC network and storage infrastructure, including MPI, NCCL, RDMA, Infiniband, and parallel file systems
• Works with scientific support specialists and assigns tasks and provides oversight as appropriate to HPC engineering team to support scientific researchers who use a broad spectrum of applications from diverse fields.
• Analyze results of server monitoring and implement changes to improve performance, processing, and utilization.
• Propose, maintain, and enforce policies, practices and security procedures.
• Provide break/fix support, setup/installation support, escalation support, and solutions support.
• Collaborate closely with a variety of stakeholders, both internal and external, on all aspects of projects.
• Other duties as assigned.
• In Addition to the Duties Described Above
• Deploy, configure, and maintain large-scale Linux-based HPC clusters comprising CPU and GPU nodes, high-speed interconnects, and parallel file systems.
• Implement and optimize workload schedulers (Slurm) and job submission policies to maximize system throughput and fair-share usage.
• Administer and monitor distributed storage systems (GPFS, Lustre, WekaFS, Ceph, MinIO) to ensure reliability and performance across multi-petabyte environments.
• Maintain high-speed fabric and network infrastructure (Infiniband, Ethernet) to support low-latency data transfer and MPI workloads.
• Support research groups in deploying, testing, and optimizing scientific applications and AI/ML workflows on shared computing resources.
• Develop and maintain automation and monitoring frameworks for system provisioning, metrics collection, and alerting (Prometheus, Grafana, ELK).