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Location
In office (Beijing)
Seniority
Intern
Visa
Sponsors visas in United States, Ireland; no register of this country names it
Employment
Internship

Confirmed on the employer's own hiring board on Nov 13, 2026. First seen by Alion on Nov 11, 2026. Intel scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Intel is an American semiconductor company founded in 1968 by Robert Noyce and Gordon Moore and headquartered in Santa Clara, California. It created the x86 instruction set that still underpins most personal computers and servers, and designs and manufactures processors, chipsets, discrete graphics, networking silicon and AI accelerators. Unlike most of its competitors the company owns its fabrication plants, and it is investing heavily in Intel Foundry to manufacture chips for external customers while rebuilding its process technology leadership.

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 / Intern

Shift:

Shift 1 (China)

Primary Location:

PRC, Beijing

Additional 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/A

Work 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.
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