Memory Architecture Research Intern

Engineering - Software San Jose, California


Position at Samsung Semiconductor, Inc.

Memory Architecture Research Intern

Summer 2020 internship applications are open November 2019 through January 2020.  Samsung Semiconductor summer internships start in May/June 2020.

Join us for a unique 12-14 week paid internship that offers personal and professional development. You’ll work with the teams that create new computing system architectures needed to support emerging machine learning applications, internet of things (IoT) and edge computing that benefit millions of users.  This program will give you the opportunity work on complex solutions to that address some of the world’s most complex technological challenges.


At Samsung Memory Solution Lab, we are at the leading edge of today’s in/near-memory solution to break-down “memory-wall” in domain specific computing. With the deepest memory portfolio in the industry, our work has widest impact to the future of heterogeneous computing system. Our research scope spans over data intensive applications, algorithms, computer architecture, memory interface and device level architecture. Currently, we are seeking a Memory Architect Intern to join our team in San Jose, CA. The candidate will participate in research project in New Memory Technology (NMT) of Memory Solutions Lab.  He or she will join a team of experts in researching and developing innovative memory computing architecture for data center acceleration/cloud computing, in memory database, and machine learning applications. The ideal candidate is a 2nd or 3rd year PhD student in CS/EECE or related field and has prior experiences in research and prototyping advanced computer architectures. This student must be comfortable working in a small group setting and problem solve at multiple levels in software and hardware.


  • Research and evaluate advanced computer architecture and memory interfaces for domain specific accelerator solution for in/near memory applications.
  • Contribute to memory and storage system performance modeling, and machine learning applications characterization.
  • Build simulation models to study the power and performance trade-offs. Explore software and hardware architectures based on their benefits to large-scale applications, contribute to feasibility studies & developing solutions.
  • Create innovative IP, publish at conferences, and generate whitepapers.


  • Good knowledge in computer architecture, including experience with some of the following: server systems, data centers, processors, cache, OS, MMU, memory hierarchy, memory subsystems, storage.
  • Strong C/C++, Python, Linux, and familiar with ML frameworks like PyTorch, TensorFlow
  • Basic hardware system profiling experiences.
  • Highly motivated with excellent verbal and written communication skills.
  • Track record of innovation and creativity in problem solving and analyzing complex system design trade-offs.
  • Good ability to debug software, prototypes, algorithms, and design experiments.
  • Good understanding of device level operations of DRAM, HBM, NVRAM and SSD.
  • Some industry or research experience is preferred.