AI GPU Arch Perf Optimization Intern

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About This Role

  • The Role and Impact As an AI Architecture and Performance Optimization Graduate Intern, you will join Intel's GPU Compute Architecture team and contribute to core GPU kernel optimization and GPU IP validation using real AI workloads.
  • Your work will directly support hardware/software codesign and help shape the performance of nextgeneration Intel GPU and AI accelerator platforms, while giving you handson exposure to GPU architecture and lowlevel 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 codesign efforts.

Requirements

  • 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.

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/job/PRC-Shanghai/AI-GPU-Arch-Perf-Optimization-Intern_JR0283576

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