Platform Power Thermal Performance Intern

About This Role

• The Role and Impact At Intel, innovation begins with the development of cutting-edge systems and solutions tailored to meet today's complex challenges.
• As a Xeon IO Performance Engineering Undergraduate Intern, you will play a vital role in developing Xeon AI performance across diverse product segments.
• Working alongside Intel's world-class engineering teams, you will gain hands-on experience applying IO engineering principles to troubleshoot, design, and optimize networks, ensuring seamless solutions for Intel's customers.
• This opportunity will allow you to build valuable skills, explore career paths, and contribute meaningfully to projects that support Intel's transformative business goals.
• Key Responsibilities You will work on a subset of the following, depending on project needs: Xeon I/O Performance Development, optimization and validation (Top-Down) Execute I/O performance validation and analyze KPIs (throughput, IOPS, latency, tail latency) and identify performance gaps across silicon/firmware/OS/driver/application layers.
• Drive debugging with hypothesis-based analysis, propose optimization ideas, and help evaluate improvements using controlled experiments.
• Identify the IO performance bottleneck and opportunities to improve IO performance per product segment.
• Product Customer Co-Validation Support Support local product I/O performance development and validation efforts, including platform-level I/O performance validation for programs such as Gem Mountain.
• Assist in China CSP customer I/O performance co-validation and contribute to performance issue closure from the PTP perspective.
• Help mitigate single-point-of-failure risk by contributing to coverage in key I/O domains (e.g., NIC, NVMe, GPU I/O related performance topics Qualifications: Minimum Qualifications Currently pursuing a Master's degree in Computer Science, Computer/Electrical Engineering, or related fields.
• Solid CPU and system architecture knowledge, especially PCIe.
• Solid Linux fundamentals (command line, process/file system basics, performance observation mindset).
• Strong analytical and problem-solving skills; ability to work independently and communicate progress/issues clearly.
• Good English verbal and writing skills to collaborate with local and global stakeholders.
• Preferred Qualifications (Nice to Have) Operating systems / kernel / storage stack / networking, AI GPU system Performance profiling methodologies and experiment Familiarity with any of the following is a plus: Storage, network, GPUs I/O benchmarking (e.g., FIO) and system performance tools Understanding of modern I/O software paths. (exposure is sufficient; deep expertise not required).
• Direct GPU AI system design and development.