INTERNSHIP DETAILS
AI GPU Arch Perf Analysis Intern
CompanyIntel Corporation
LocationBeijing
Work ModeOn Site
PostedNovember 11, 2026

Internship Information
Core Responsibilities
The intern will analyze and optimize core GPU compute kernels for AI workloads and contribute to hardware/software co-design. They will also perform performance profiling to identify bottlenecks and provide insights to support GPU architecture design.
Internship Type
full time
Company Size
109683
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
Our mission is to shape the future of technology to help create a better future for the entire world, that’s the power of Intel Inside. With more ingenuity and creativity inside, our work is at the heart of countless innovations. From major breakthroughs to things that make everyday life better— they’re all powered by Intel technology. With a career at Intel, you can help make the future more wonderful for everyone.
• Need help or have a support question? Visit Intel Support: http://ms.spr.ly/6054tmaop
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About the Role
Job Details:
Job Description:
As an AI Architecture Performance Analysis Graduate Intern, you will join Intel's GPU Compute Architecture team and contribute to core GPU kernel perf analysis using real AI workloads. Your work will directly support hardware/software co design and help analyze and shape the performance of next generation Intel GPU and AI accelerator platforms, while giving you hands on exposure to GPU architecture and low level performance engineering. Key Responsibilities • Analyze and optimize core GPU compute kernels for AI and numerical workloads (e.g., GEMM, Attention, operator fusion). • Reproduce representative AI inference and training workloads for GPU IP validation. • Perform GPU performance profiling and analysis to identify compute, memory, and pipeline bottlenecks. • Build performance profiles and models to understand architecture level performance behavior. • Provide workload and kernel level insights to support GPU architecture design and HW/SW co design efforts.Qualifications:
Minimum Qualifications • Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field. • Proficiency in Python for analysis, experimentation, or tooling. • Solid understanding of AI fundamentals, including common models and algorithms. • Strong interest in GPU architecture, GPU programming, parallel computing, and performance optimization. • Basic knowledge of computer systems, such as CPU/GPU architecture, memory systems, and performance analysis. Preferred Qualifications • Experience with GPU kernels or programming models (e.g., CUDA, OpenCL, SYCL, Triton). • Exposure to performance optimization, compiler, or parallel computing coursework, research, or internships. • Strong analytical and problem solving skills, with the ability to reason from profiling data. • Interest in AI systems and infrastructure, beyond model level development. • Ability to work effectively in a collaborative, cross functional engineering environment.
Job Type:
Student / InternShift:
Shift 1 (China)Primary Location:
PRC, BeijingAdditional Locations:
Posting Statement:
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.Position of Trust
N/AWork Model for this Role
This role will require an on-site presence. * Job posting details (such as work model, location or time type) are subject to change.*
ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.Key Skills
PythonGPU ArchitecturePerformance AnalysisAI FundamentalsParallel ComputingCUDAOpenCLSYCLTritonPerformance ProfilingComputer EngineeringNumerical WorkloadsGEMMAttention MechanismsOperator Fusion
Categories
TechnologyEngineeringSoftwareData & AnalyticsScience & Research
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