Senior System Engineer – GPU Platforms

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

• 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

Requirements

• Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science, Information Technology, or a related discipline, 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 a 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 high-performance computing 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

Core Competencies

Demonstrates expertise in GPU server platform support, including installation, configuration, and troubleshooting of Linux environments and GPU technologies. Proficient in system-level diagnostics, technical documentation, and cross-functional collaboration to drive complex technical assignments to resolution.

Highest-signal resume keywords

• GPU Computing
• Linux Server Environments
• System-Level Troubleshooting
• NVIDIA NVQUAL
• Technical Documentation

Hard Skills

• GPU Drivers
• CUDA
• Server Hardware Configuration
• Root-Cause Analysis
• PCIe Architectures
• High-Performance Computing
• NVIDIA Data Center Platforms
• Docker
• Python Scripting
• Bash Scripting

Soft Skills

• Strong Communication Skills
• Cross-Functional Collaboration
• Customer-Facing Technical Discussions
• Mentoring

Industry Keywords

• Systems Engineering
• Server Engineering
• Platform Engineering
• Technical Enablement
• AI Infrastructure
• HPC

Tools & Technologies

• NCCL
• NVML
• DCGM
• Fabric Manager
• InfiniBand
• RoCE
• High-Speed Ethernet
• Kubernetes