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Posted 4 hours ago
Member of Technical Staff - GPU Infrastructure
Prime IntellectMember of Technical Staff - GPU Infrastructure
Requirements
3+ years GPU cluster/HPC experience, Expertise in SLURM and Kubernetes, InfiniBand configuration experience, NVIDIA GPU architecture knowledge, Ansible and Terraform proficiency, Python and Bash proficiency
Skills
GPUKubernetesCUDAPython
About the role
About the Company
Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. We have raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators.
Responsibilities
- Partner with clients to design optimal GPU cluster architectures and create technical proposals for clusters ranging from 100 to 10,000+ GPUs
- Deploy and configure orchestration systems including SLURM and Kubernetes for distributed workloads
- Implement high-performance networking with InfiniBand, RoCE, and NVLink interconnects
- Optimize GPU utilization, memory management, and inter-node communication
- Configure parallel filesystems like Lustre, BeeGFS, or GPFS for optimal I/O performance
- Serve as the primary technical escalation point for customer infrastructure issues across hardware, drivers, networking, and software
- Implement monitoring, alerting, and automated remediation systems
Requirements
- 3+ years hands-on experience with GPU clusters and HPC environments
- Deep expertise with SLURM and Kubernetes in production GPU settings
- Proven experience with InfiniBand configuration and troubleshooting
- Strong understanding of NVIDIA GPU architecture, CUDA ecosystem, and driver stack
- Experience with infrastructure automation tools such as Ansible and Terraform
- Proficiency in Python, Bash, and systems programming
- Track record of customer-facing technical leadership
- Experience with NVIDIA driver installation and troubleshooting (CUDA, Fabric Manager, DCGM)
- Knowledge of container runtime configuration for GPUs (Docker, Containerd, Enroot)
Preferred Qualifications
- Experience with 1000+ GPU deployments
- NVIDIA DGX, HGX, or SuperPOD certification
- Experience with distributed training frameworks like PyTorch FSDP, DeepSpeed, or Megatron-LM
- ML framework optimization and profiling experience
- Experience with AMD MI300 or Intel Gaudi accelerators
- Contributions to open-source HPC/AI infrastructure projects
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Get started — it's freeMember of Technical Staff - GPU Infrastructure
Prime Intellect · San Francisco
