Job Description:
Join as a GPU AI Compute Architect Intern and contribute to shaping the future of Intel’s AI hardware. This role involves analyzing AI workloads, developing performance analysis tools, and evaluating GPU AI architecture to optimize next-generation Intel hardware.

Responsibilities:

  • Analyze performance data for emerging AI workloads, including multimodality generative AI
  • Co-develop and enhance internal performance analysis tools for better accuracy
  • Correlate simulation results with real hardware measurements
  • Evaluate GPU AI hardware architecture to improve efficiency
  • Provide software optimization guidelines for AI workloads

Preferred Qualifications:

  • Strong data analysis and presentation skills
  • Understanding of deep learning models like LLM and Stable Diffusion
  • Experience with performance analysis tools and simulators
  • Knowledge of computer architecture and workload characterization
  • Familiarity with PyTorch and AI software frameworks

Education Requirement: Pursuing or completed BS, MS in Electrical Engineering, Computer Science, Mathematics, or related majors

Technical Skills Required: Python, AI, Deep Learning, Large Language Models (LLM), Stable Diffusion, Multimodality Generative AI, Performance Analysis Tools, Simulators, Workload Characterization, Performance Projection, Computer Architecture, PyTorch

This internship offers an exciting opportunity to work in AI hardware research and development, gaining hands-on experience with cutting-edge GPU and AI computing technologies.