Intern - Emerging Memory (Summer 2026)
Overview
Posted
3 weeks ago
Internship Type
Remote Status
Location
San Jose, CA, US
Education Level
Education Status
Not specified
Categories
Tags
Not specified
Job Title: Intern - Emerging Memory (Summer 2026)
Office Location: San Jose, CA
Work Model: Onsite
Duration: May 2026 - July 2026
Work Model: Onsite
Duration: May 2026 - July 2026
At SK hynix America, we're at the forefront of semiconductor innovation, developing advanced memory solutions that power everything from smartphones to data centers. As a global leader in DRAM and NAND flash technologies, we drive the evolution of advancing mobile technology, empowering cloud computing, and pioneering future technologies. Our cutting-edge memory technologies are essential in today's most advanced electronic devices and IT infrastructure, enabling enhanced performance and user experiences across the digital landscape.
We're looking for innovative minds to join our mission of shaping the future of technology. At SK hynix America, you'll be part of a team that's pioneering breakthrough memory solutions while maintaining a strong commitment to sustainability. We're not just adapting to technological change – we're driving it, with significant investments in artificial intelligence, machine learning, and eco-friendly solutions and operational practices. As we continue to expand our market presence and push the boundaries of what's possible in semiconductor technology, we invite you to be part of our journey to creating the next generation of memory solutions that will define the future of computing.
Position Summary:
We are seeking a highly motivated research intern to work on AI system architectures and applications based on emerging memory technologies. The intern will contribute to research on memory-centric AI systems, spanning device characteristics, architecture design, and system-level evaluation.
Responsibilities:
- Conduct research on emerging memory technologies and their implications for AI systems
- Analyze and model memory behavior, bandwidth, latency, and energy efficiency in AI workloads
- Assist in the design and evaluation of memory-centric or near-/in-memory AI architectures
- Support AI system simulation, modeling, or prototyping at the architecture or system level
- Review and summarize relevant academic literature and technical reports
- Collaborate with researchers to prepare technical reports, presentations, or publications
Minimum Qualifications:
- Master's degree in Electrical Engineering, Computer Engineering, or a related field
- Basic understanding of AI systems, machine learning workloads, or computer architecture
- Fundamental knowledge of memory systems or semiconductor devices
- Strong analytical and problem-solving skills
- Experience with at least one programming or modeling tool (e.g., Python, C/C++, MATLAB)
Preferred Qualifications:
- Ph.D. in a relevant field with research experience in emerging memory
- Experience with architecture simulators, system modeling tools, or AI frameworks
- Understanding of AI workload characteristics (training vs. inference, data movement bottlenecks, memory hierarchy)
- Prior research experience or publications in related areas
- Interest in cross-layer research spanning devices, architecture, and AI applications
Housing Allowance:
Eligible interns will receive a housing allowance during their internship.
Equal Employment Opportunity:
SKHYA is an Equal Employment Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type without regard to race, sex, pregnancy, sexual orientation, religion, age, gender identity, national origin, color, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws.
SKHYA is an Equal Employment Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type without regard to race, sex, pregnancy, sexual orientation, religion, age, gender identity, national origin, color, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws.
Compensation:
Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. Pay within the provided range varies by work location and may also depend on job-related skills and experience. Your Recruiter can share more about the specific salary range for the job location during the hiring process.
Pay Range
$26—$50 USD