Platform Power Thermal Performance Engineer

Intel
Shanghai
Workplace: OnsiteFull timeFunction: Energy & Utilities OperationsEducation: mastersSkills: ["Learning agility","Problem-solving","Teamwork","Communication","Technical documentation"]

Contribute to GPU-as-an-I/O-device performance validation for AI server platforms, working across CPU host architecture, I/O subsystems, GPU interactions, and server-level performance analysis. Build and refine validation methodologies, execute benchmark experiments, collect and analyze results, and help investigate technical issues across reference designs and customer-oriented systems. Partner with experienced engineers and cross-functional teams to document findings, communicate progress, and support issue closure.

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FursaFursa
Intel
Intel
2 hours ago

Platform Power Thermal Performance Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Contribute to GPU-as-an-I/O-device performance validation for AI server platforms, working across CPU host architecture, I/O subsystems, GPU interactions, and server-level performance analysis. Build and refine validation methodologies, execute benchmark experiments, collect and analyze results, and help investigate technical issues across reference designs and customer-oriented systems. Partner with experienced engineers and cross-functional teams to document findings, communicate progress, and support issue closure.
Location: Shanghai
Workplace: Onsite
Employment Type: Full time
Job Function: Energy & Utilities Operations
Seniority: Graduate level

Key Responsibilities

  • •Learn and contribute to topology validation and performance analysis for AI server platforms, covering CPU host, GPU, memory, storage, and network interactions.
  • •Support validation plan development, benchmark execution, data collection, and result analysis for CPU host and GPU I/O performance studies.
  • •Debug performance issues with senior engineers, summarize findings, and propose practical improvement ideas from the host platform perspective.
  • •Collaborate with cross-functional teams to communicate test progress, document technical observations, and support issue closure under guidance.

Key Requirements

  • •Master of Science (or higher) in Electrical Engineering, Computer Science, Computer Engineering, or a related technical field.
  • •Solid fundamentals in computer architecture, operating systems, or computer systems, with interest in CPU, memory, and I/O subsystem behavior.
  • •Basic understanding of GPU computing, parallel programming, or accelerator-based systems (related coursework/research/projects a plus).
  • •Interest in AI infrastructure and at-scale system concepts, including server architecture, scale-up/scale-out design, networking, and storage.
  • •Programming/scripting ability (Python, C/C++, or shell scripting) and familiarity with benchmarking methodology, performance metrics, and experiment design.
Experience:AI infrastructureGPU computingMachine learning/deep learning workloadsLinux-based developmentBenchmarkingSystem validation
Education:Master's
Skills:Learning agilityProblem-solvingTeamworkCommunicationTechnical documentation
Languages:English
Tech Stack:PythonC/C++Shell scriptingCUDAROCmOpenCLSYCLLinuxPCIe/CXLIOMMUNUMABenchmarking

Company Brief

Intel
Designs and manufactures semiconductor chips, processors, and related hardware for PCs, data centers, networking, and embedded applications, while providing software and services to accelerate computing across industries globally.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1968
Glassdoor
Glassdoor: 3.8
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