Job Details:Job Description:Role OverviewJoin our Silicon Architecture team as an undergraduate intern and contribute to the development of next-generation computing platforms. In this role, you will support architecture definition, performance analysis, and power optimization across silicon systems, including hardware, firmware, and platform-level solutions.
This internship provides hands-on experience working alongside architects, design engineers, and validation teams to solve real-world challenges in CPU/SoC architecture and AI-driven technologies.
What You'll ExperienceKey Responsibilities
- Assist in defining and analyzing silicon and system architectures (CPU, SoC, and platform-level design)
- Support modeling, simulation, and analysis of performance, power, and feature trade-offs
- Collaborate cross-functionally with architecture, design, and validation teams
- Contribute to feasibility studies and early-stage product definition
- Perform data analysis, debugging, and performance optimization
- Explore applications of AI/ML techniques in architecture and system design
Behavioral Traits that we are looking for:- Curiosity: Eager to learn new technologies and explore unfamiliar problems
- Initiative: Takes proactive steps to contribute and ask questions
- Collaboration: Works well in team environments and values diverse perspectives
- Analytical Thinking: Able to break down complex problems into manageable parts
- Adaptability: Comfortable navigating ambiguity and evolving priorities
- Communication: Clearly communicates technical ideas and findings
- Growth Mindset: Open to feedback and continuously developing skills
What You Will Gain- Hands-on experience applying AI to real-world security challenges
- Mentorship from experienced engineers and researchers
- Exposure to industry tools, workflows, and best practices
- Opportunity to contribute to meaningful, impactful projects
Qualifications:You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. Experience would be obtained through a combination of prior education level classes, and current level school classes, projects, research, and relevant previous job and/or internship experience.
Note: This position is not eligible for Intel immigration sponsorship.Minimum Qualifications and Experience:
Currently pursuing a Bachelor's degree in Electrical Engineering, Computer Engineering, or a related field.
Must be available to participate in a full-time internship for a minimum duration of six (6) consecutive months.
Must have 3+ months of educational or work experience in the following:
- Computer Architecture fundamentals
- Data analysis and debugging
- Machine learning
- Python programming
Preferred Qualifications and Experience:
- Experience with power and performance analysis methodologies.
- Familiarity with performance optimization techniques.
- Understanding of artificial intelligence, neural networks, or AI-related workloads.
Job Type:Student / Intern
Shift:Shift 1 (United States of America)
Primary Location:US, California, Folsom
Additional Locations:BenefitsWe offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.
Annual Salary Range for jobs which could be performed in the US: $77,300.00-104,600.00 USD (Hourly Role)
The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Our standard internship rates are based on your degree, location, and the job role. Your recruiter can share more about the specific compensation range for your preferred location and job role during the hiring process.
Work Model for this RoleThis role will require an on-site presence. * Job posting details (such as work model, location or time type) are subject to change.
