Research Computing GPU Systems Engineer
S
Stanford University
📍 Stanford, CA, United States
Job Description
**Job Description**
**About the Role**
Stanford Research Computing seeks an exceptional GPU Cluster Lead Engineer to oversee technical operations, optimization, and strategic development of Marlowe, Stanford's NVIDIA SuperPOD. This role combines deep technical expertise in GPU computing, large-scale cluster management, and leadership in supporting a diverse research community. You will serve as the technical authority on GPU infrastructure, driving system performance and reliability while enabling groundbreaking research in AI/ML, computational biology, physics, and beyond.
**Key Responsibilities**
**System Operations & Management**
+ Lead day-to-day operations of the GPU Cluster, ensuring optimal uptime and performance.
+ Architect monitoring, alerting, and observability solutions using Prometheus, Grafana, DCGM, and Base Command Manager.
+ Manage job scheduling and resource allocation using Slurm, implementing advanced GPU partitioning and confi...
**About the Role**
Stanford Research Computing seeks an exceptional GPU Cluster Lead Engineer to oversee technical operations, optimization, and strategic development of Marlowe, Stanford's NVIDIA SuperPOD. This role combines deep technical expertise in GPU computing, large-scale cluster management, and leadership in supporting a diverse research community. You will serve as the technical authority on GPU infrastructure, driving system performance and reliability while enabling groundbreaking research in AI/ML, computational biology, physics, and beyond.
**Key Responsibilities**
**System Operations & Management**
+ Lead day-to-day operations of the GPU Cluster, ensuring optimal uptime and performance.
+ Architect monitoring, alerting, and observability solutions using Prometheus, Grafana, DCGM, and Base Command Manager.
+ Manage job scheduling and resource allocation using Slurm, implementing advanced GPU partitioning and confi...