Staff Engineer, GPU Front-End Infrastructure/ Methodology

Samsung Electronics•Austin, TX

4d•$151,000 - $226,600•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! Role and Responsibilities As a Staff GPU Front-End Implementation Methodology Engineer, you will shape and advance the front-end implementation methodologies that underpin high-quality, scalable RTL across complex GPU and SoC designs. Working as a mid-to-senior individual contributor, you will serve as a key enabler for design and verification teams — helping them work faster, with greater confidence, and at scale. You will partner closely with architecture, verification, CAD, and physical design groups to define and uphold best practices, design guidelines, and quality standards that align with high-performance and low-power goals. You will own and evolve the RTL flow and build system, including support for an agentic AI workflow, and contribute to a broader portfolio of software initiatives: the RTL CI/CD system, operational metrics collection and reporting, custom web application development, and open-source tool provisioning. In this role, you will: Empower design and DV teams to work efficiently by removing friction from front-end workflows and proactively addressing methodology gaps Drive front-end RTL implementation methodologies for GPU and SoC designs, ensuring scalability, architectural alignment, and adherence to performance and power objectives Take ownership of moderate-to-complex projects, leading efforts to advance best practices and staying ahead of industry trends and emerging technologies

Requirements

6+ years of experience with a Bachelor’s Degree in Computer Science/Engineering, or 4+ years of experience with a Master’s Degree, or 2+ years of experience with a Ph.D.
Hands-on experience designing and building agentic AI tools and workflows
Proficiency across a broad range of Unix/Linux programming languages, including Python, C++, Perl, Ruby, Go, and shell scripting
Deep Linux system expertise, including debugging complex system-level issues
Solid background in DevOps practices, build automation, and build systems, including GNU Make
Experience with containerized environments and orchestration platforms, including Docker, Kubernetes, and OpenShift
Strong analytical and problem-solving skills with a methodical approach to debugging
Excellent written and verbal communication skills, with a track record of producing clear technical documentation, design specs, and methodology guides
Proven ability to collaborate effectively across global, cross-functional teams and thrive in fast-paced, ambiguous environments

Nice To Haves

Familiarity with RTL design concepts and testbench environments is a plus

Responsibilities

Empower design and DV teams to work efficiently by removing friction from front-end workflows and proactively addressing methodology gaps
Drive front-end RTL implementation methodologies for GPU and SoC designs, ensuring scalability, architectural alignment, and adherence to performance and power objectives
Take ownership of moderate-to-complex projects, leading efforts to advance best practices and staying ahead of industry trends and emerging technologies