Engineer

Samsung Electronics•San Jose, CA

8d•$160,197 - $208,440•Onsite

About The Position

Samsung, a world leader in advanced semiconductor technology, is founded on a simple philosophy – the endless pursuit of excellence will create a better world for all. At Samsung Austin Research and Development Center (SARC) and Advanced Computing Lab (ACL), we are building a center of excellence for Intellectual Property (IP) that is applied to high-performance computing devices (mobile, automotive, and other custom market segments) consumed by millions of people around the world. Come build with us!

Requirements

Master’s degree or foreign equivalent in Computer Engineering, Electrical Engineering or a closely related field.
Completion of a graduate level course, research project, or internship involving the following: High performance processors: Pipelining, Parallelism techniques, memory hierarchies.
Completion of a graduate level course, research project, or internship involving the following: Techniques for Quantitative analysis and evaluation of computing systems and compare alternate design choices.
Completion of a graduate level course, research project, or internship involving the following: Machine learning Approaches (Python Programming).
Completion of a graduate level course, research project, or internship involving the following: Logic synthesis and design methodology: Front and back-end design flows.
Employer will accept skills gained in pursuit of university-level degree via coursework, projects, or internships. Skills may be gained concurrently.

Responsibilities

Perform semiconductor engineering research, design, development, and/or testing for firm products and/or devices for use in the electronic communication industry.
Design and document major units in a GPU pipeline targeted at mobile graphics and machine learning.
Drive and develop the functional and cycle simulators for GPU pipeline.
Collect statistics to evaluate potential benefit of optimizations, prototype to test functional correctness and specify the scheme in detail for next level of implementation in hardware and/or software.
Collaborate with implementation, modeling, and software teams to define and develop microarchitecture, software implementation, and/or a verification plan.
Investigate alternate approaches for important GPU workloads, incremental optimizations, and rebalancing to maximize performance in future key workloads.
Work with software developers to understand important trends in future graphics and AI applications, problems faced by application and middleware developers.
Identify and implement applications to exercise novel algorithms in drivers/hardware.