GPU Architecture Graduate Intern

Intel Corporation•Folsom, CA

4d•$105,698 - $105,702•Onsite

About The Position

As a Silicon Architecture Graduate Intern, you will contribute to defining and architecting silicon solutions, including hardware, firmware, and platform specifications. You will assist with modeling and simulation to analyze performance, power, and feature trade-offs across interconnected subsystems, supporting architectural decisions that meet product goals. You will collaborate with architects, design engineers, and validation teams on early-stage feasibility and specification development. The role is part of Intel’s Data Center Group, a global organization focused on scalable and efficient solutions for digital infrastructure and advanced computing. You will gain hands-on experience and contribute to technologies for high-performance computing and data solutions.

Requirements

Pursuing a master's degree in GPU architecture, Computer Engineering, Electrical Engineering, or a closely related field.
Knowledge of GPU architecture concepts, including SIMT, parallelism, and cache hierarchies.
Proficiency in C, C++, and Python programming.
Understanding of hardware pipelines and basic RTL design methodologies.
Minimum GPA of 3.0.

Nice To Haves

Strong problem-solving and analytical skills to address complex technical challenges.
Excellent communication and teamwork abilities for working in a collaborative environment.
Enthusiasm to learn and grow within Intel's ecosystem and contribute to impactful technologies.

Responsibilities

Assist in defining silicon architecture specifications based on product requirements and feature integration.
Support modeling and simulation tasks to evaluate performance, power, and trade-offs for architectural decisions.
Collaborate with architects, design engineers, and validation teams to ensure feasibility and alignment with product goals.
Contribute to developing high-level models and tools for architectural analysis.
Explore GPU concepts such as SIMT, parallelism, and cache hierarchies to guide architectural improvements.
Use C, C++, and Python programming for prototyping and analysis tasks.