We are seeking a highly motivated undergraduate intern to join the GPU Client AI team and contribute to AI inference performance optimization on Intel GP - Us. This is a hands-on, technical internship designed for students who want deep exposure to real-world AI workloads, GPU performance optimization, and systems-level software engineering. This role is ideal for a student who can work part-time (~16 hours/week) for 6 months to 1 year and is interested in building strong foundations in AI software stacks, GPU programming, and performance optimization. What You Will Do. As an intern, you will work closely with senior engineers and gradually take ownership of well-scoped technical tasks, such as: - Assist in profiling and benchmarking AI inference workloads (e.g., LL - Ms, vision models) on Intel GP - Us - Support analysis of performance bottlenecks across compiler, runtime, and kernel layers under guidance - Contribute to C codebases related to AI runtimes, tooling, or performance experiments - Learn and apply best practices in debugging, performance measurement, and code quality in a production environment. What You Will Learn. This internship provides exposure to: - AI inference software stacks and how modern models map onto GPU hardware - Basics of GPU architecture and parallel programming concepts - Performance profiling tools and methodology for data-driven optimization - Real-world engineering workflows: code reviews, design discussions, and cross-team collaboration. This position is not eligible for Intel immigration sponsorship. Qualifications:Minimum Qualifications - Currently pursuing a Bachelor's degree in Computer Science or a related field - Strong fundamentals in C - Coursework or projects involving Parallel programming or Machine learning - Ability to work ~16 hours per week for 6 months or longer - Strong problem-solving skills and eagerness to learn Preferred Qualifications (Nice to Have) - Exposure to machine learning or AI frameworks through coursework or projects (e.g., Py. Torch, Tensor. Flow, Open. VINO) - Basic understanding of GPU programming concepts (e.g., SIMD, threading, memory hierarchies) - Prior internship, research, or class projects related to performance optimization or systems programming - Interest in AI performance, compilers, runtimes, or hardware-software co-optimization Job Type:Student / Intern. Shift:Shift 1 (United States of America)Primary Location: US, California, Folsom.