Qualcomm
Hardware (CPU, GPU, SoC, Digital Design, DV) Engineering Internship – Summer 2027
San Diego, California +4 · On-site · Internship · Posted Sep 18, 2026
- Location
- San Diego, California
Austin, Texas
Boxborough, Massachusetts
Tempe, Arizona
Santa Clara, California - Experience
- 1+ years of academic experience with programming languages; internship duration is 11–14 weeks.
- Education
- Currently enrolled in a bachelor’s, master’s, or Ph.D. degree program in computer engineering, computer science, electrical engineering, or a related field.
- Visa sponsorship
- The internship aligns to a potential role that is not eligible for Qualcomm immigration sponsorship.
About the job
Contributes to Qualcomm hardware engineering projects across GPU, CPU, digital design/verification, or SoC systems, supporting design, modeling, validation, and related engineering work.
What you'll do
- Work on a multidisciplinary hardware team in areas such as architecture, RTL, implementation, design-for-test, physical design, verification, emulation, validation, CAD, or GPU design.
- Contribute to track-specific work such as developing and verifying designs, modeling system performance, or validating hardware.
- Indicate track interests in the resume for recruiting consideration.
What they ask for
- Currently enrolled in a bachelor’s, master’s, or Ph.D. program in computer engineering, computer science, electrical engineering, or a related field.
- Available for 11–14 weeks during Summer 2027 (May–September).
- Expected graduation date of November 2027 or later.
- 1+ years of academic experience with programming languages such as C, C++, Python, Perl, Verilog, SystemVerilog.
Nice to have
- Currently enrolled in a Master’s or PhD program in computer engineering, electrical engineering, or a related field.
- Track-specific knowledge or experience, including CPU/GPU/SoC architecture, digital design and verification, wireless technologies, or machine learning workloads on embedded systems.
Pay
$17.00 - $98.00 (hourly pay; currency not stated)
Tools
C, C++, Python, Perl, Verilog, SystemVerilog, UVM, Vulkan
AI focus
Some SoC Systems Engineering work involves supporting or optimizing machine learning workloads on embedded systems or accelerators; exposure to machine learning for digital signal processing or modem architecture is a plus.
Model-written summary · the original posting is authoritative