GPU Platform SME

Position Overview

Lenovo Infrastructure Solutions Group (ISG) is seeking a highly motivated GPU Systems Validation Engineer to help develop and validate next-generation AI and accelerated computing platforms.

In this role, you will work at the forefront of AI infrastructure, validating cutting-edge GPU technologies across server, rack, and cluster environments. You will partner with GPU architects, hardware and firmware engineering teams, and industry-leading technology suppliers to ensure platform readiness, performance, reliability, and scalability for enterprise and hyperscale AI deployments.

This is an excellent opportunity for engineers with hands-on experience validating NVIDIA HGX/DGX platforms, high-performance servers, AI infrastructure, GPU clusters, InfiniBand fabrics, rack-scale systems, and large-scale data center deployments who enjoy solving complex technical problems and driving issues through root cause and resolution.

Job Responsibilities

GPU Platform Architecture & Validation Strategy

• Study next-generation GPU platform architectures, reference designs, and supplier documentation to understand platform capabilities, design changes, and validation requirements.
• Perform comparative analysis between incoming and outgoing platform generations, identifying validation impacts, readiness gaps, risks, and infrastructure requirements.
• Review supplier validation requirements (such as NVIDIA platform validation programs) and Lenovo validation strategies to determine execution prerequisites and validation coverage plans.
• Work closely with GPU architects and engineering stakeholders to translate platform requirements into executable validation strategies.

Validation Readiness & Infrastructure Planning

• Define and coordinate validation environment requirements, including lab infrastructure, test equipment, fixtures, software tools, utilities, licenses, and system configurations required for successful execution.
• Review Lenovo validation plans and test requirements across multiple engineering disciplines, including Platform Architecture, Electrical Engineering, Enterprise Architecture, Thermal Engineering, and Reliability Engineering.
• Partner with engineering teams to establish validation readiness plans for new platform introductions and technology transitions.
• Support validation framework deployment and test environment setup activities across server, rack, and cluster environments.

System Bring-Up & Process Development

• Collaborate with GPU architects and engineering teams to develop system bring-up processes, work instructions, validation procedures, and standard operating procedures (SOPs).
• Establish test methodologies, execution processes, and validation best practices to ensure consistent and repeatable test results.
• Support platform integration activities and validation environment preparation throughout the product development lifecycle.

Validation Execution & Test Ownership

• Lead validation activities for next-generation GPU-enabled server platforms at the node (L10), rack (L11), and cluster (L12) levels.
• Execute system integration, functional, stress, performance, scalability, and reliability testing for advanced AI and accelerated computing platforms.
• Develop and execute validation plans covering hardware, firmware, operating systems, networking, storage, management controllers, device drivers, and GPU subsystems.
• Validate AI infrastructure technologies including GPU interconnects, high-speed networking fabrics, rack integration, power delivery systems, cooling solutions, and cluster deployments.

Failure Analysis, Debug & Root Cause Investigation

• Own technical issues throughout the complete validation lifecycle, including issue discovery, triage, experiment design, failure reproduction, root cause analysis, corrective action identification, and validation closure.
• Investigate complex hardware, firmware, software, and infrastructure issues using log analysis, diagnostics, system telemetry, and structured debugging techniques.
• Perform technical experiments and data-driven analysis to isolate failures and determine root cause.
• Drive issue resolution with cross-functional engineering teams and ensure corrective actions are properly validated.

Cross-Functional & Supplier Collaboration

• Collaborate closely with Platform Architecture, Electrical Engineering, Thermal Engineering, Reliability Engineering, Software Engineering, Manufacturing Engineering, and Product Development teams.
• Partner directly with GPU suppliers and engineering counterparts on product-specific issues, validation findings, failure analysis, corrective actions, and technical escalations.
• Work effectively with global engineering organizations, ODM/OEM partners, hyperscale customers, and technology suppliers to achieve validation and product quality objectives.
• Support technical reviews, milestone readiness assessments, and product release activities.

Job Requirements

Required Qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, Computer and Information Science, or a related technical discipline.
• 6+ years of experience in server platform development, system validation, system integration, hardware validation, AI infrastructure, or related engineering disciplines.
• Strong knowledge of enterprise server architecture and system integration, including:
• BIOS/UEFI
• Baseboard Management Controllers (BMC)
• Operating systems
• CPU and memory subsystems
• Storage technologies
• Networking technologies
• PCIe devices
• Firmware
• Device drivers
• Software applications
• Strong understanding of GPU interconnect and high-speed networking technologies, including:
• PCIe
• Ethernet
• InfiniBand
• NVLink
• NVSwitch
• Related GPU fabric technologies
• Hands-on experience performing:
• System integration testing
• Functional validation
• Stress testing
• Performance testing
• Failure analysis
• Troubleshooting and root cause investigations
• Working knowledge of Linux administration, command-line diagnostics, log analysis, and server troubleshooting methodologies and tools.
• Demonstrated ability to independently drive complex technical issues from identification through root cause determination and resolution.
• Strong written and verbal communication skills with the ability to collaborate effectively across global cross-functional engineering teams.

Preferred Qualifications

• Hands-on experience with one or more advanced AI infrastructure platforms, including:
• NVIDIA HGX
• NVIDIA DGX
• GB200
• GB300
• NVL72
• Next-generation GPU architectures
• Experience with rack-scale AI systems, GPU clusters, and large-scale accelerated computing environments utilizing:
• NVLink
• NVSwitch
• InfiniBand fabrics
• High-speed Ethernet fabrics
• Experience supporting hyperscale, cloud, AI infrastructure, OEM, ODM, server development, manufacturing validation, or large-scale data center deployments.
• Familiarity with NVIDIA validation and diagnostic tools, including:
• DCGM
• NVDiag
• NVQual
• Experience with NVIDIA CUDA, AMD ROCm, or other GPU software ecosystems.
• Experience developing validation automation, diagnostic solutions, or validation frameworks using Python, Shell scripting, or similar programming languages.
• Familiarity with liquid cooling infrastructure, power distribution systems, rack integration technologies, and data center deployment considerations.
• Experience collaborating directly with GPU suppliers, hyperscale customers, ODM/OEM partners, or global engineering organizations.
• Mandarin language capability is highly preferred due to collaboration with global engineering teams and supplier partners.