Senior GPU Platform Engineer – Linux, NVQUAL & HPC

Jobtailor; San Jose (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Jobtailor in San Jose, CA seeks a Senior GPU Platform Systems Engineer to lead support, qualification, and deployment of enterprise GPU server platforms. You will diagnose complex issues, coordinate with cross-functional teams, and mentor junior engineers.

The role requires 5–15 years in systems engineering or HPC, strong Linux experience, and hands-on GPU/CUDA expertise. Preferred: NVIDIA NVQUAL and Docker/Kubernetes familiarity.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5–15 years of relevant industry experience in systems engineering, server engineering, platform engineering, validation, technical enablement, HPC, AI infrastructure, or related field.
• Strong knowledge of enterprise server hardware and system architecture.
• Hands-on experience with Linux server environments.
• Experience installing, configuring, validating, and troubleshooting server hardware and software.
• Strong system-level troubleshooting and root-cause-analysis skills.
• Working knowledge of PCIe architectures and high-performance I/O.
• Experience with GPU computing, accelerators, or comparable HPC technologies.
• Ability to independently manage complex technical assignments and drive issues toward resolution.
• Strong written and verbal communication skills.
• Ability to work effectively with cross-functional and geographically distributed engineering teams.
• Comfortable participating in customer-facing technical discussions.
• Preferred: Hands-on experience with NVIDIA data center or professional GPU platforms.
• Preferred: Experience with CUDA and NVIDIA GPU software environments.
• Preferred: Experience with NVIDIA NVQUAL or similar platform qualification processes.
• Preferred: Experience with 4-GPU or 8-GPU server platforms.
• Preferred: Familiarity with NVIDIA Blackwell, B200, Rubin or comparable accelerator architectures.
• Preferred: Knowledge of PCIe topology, NUMA, DMA, IOMMU, and GPU-to-NIC communication.
• Preferred: Experience with GPUDirect RDMA, InfiniBand, RoCE, or high-speed Ethernet.
• Preferred: Familiarity with NCCL, NVML, DCGM, Fabric Manager, or similar GPU diagnostic and management tools.
• Preferred: Experience with Docker, containers, Kubernetes, or related orchestration technologies.
• Preferred: Experience supporting AI, machine learning, HPC, or accelerated computing environments.
• Preferred: Experience with customer POCs, technical evaluations, or engineering escalations.
• Preferred: Experience delivering technical training or knowledge-sharing sessions.
• Bash, Python, or other scripting experience is a plus.

Responsibilities

• Support system bring-up, configuration, integration, validation, and troubleshooting of advanced GPU server platforms.
• Execute and support GPU platform qualification activities, including NVIDIA NVQUAL or equivalent validation processes.
• Install, configure, and troubleshoot Linux, GPU drivers, CUDA environments, firmware, libraries, and related software components.
• Diagnose complex system issues using logs, telemetry, diagnostics, and vendor tools, and drive issues to resolution or appropriate engineering escalation.
• Support multi-GPU server platforms throughout qualification, product launch, and post-release engineering activities.
• Participate in customer-facing POC/EVAL engagements, including system preparation, technical calls, debugging, and issue resolution.
• Collaborate with Architecture, Systems, Software, Validation, Product Management, other engineering teams, and external technology partners.
• Develop technical documentation, troubleshooting guides, and best practices.
• Deliver technical presentations, training sessions, and internal knowledge-sharing activities.
• Serve as a technical resource and mentor for other engineers when appropriate.

Skills

Linux Server Environments

System-Level Troubleshooting

PCIe Architectures

High-Performance Computing

NVIDIA Data Center Platforms

Python Scripting

Bash Scripting

GPU Computing

Cross-Functional Collaboration

Customer-Facing Technical Discussions

Education

Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science, Information Technology, or related discipline

Tools

Docker

Kubernetes

NVIDIA NVQUAL

CUDA

Job description

Jobtailor in San Jose, CA seeks a Senior GPU Platform Systems Engineer to lead support, qualification, and deployment of enterprise GPU server platforms. You will diagnose complex issues, coordinate with cross-functional teams, and mentor junior engineers.

The role requires 5–15 years in systems engineering or HPC, strong Linux experience, and hands-on GPU/CUDA expertise. Preferred: NVIDIA NVQUAL and Docker/Kubernetes familiarity.