Senior Engineer, GPU Graphic Core Verification

Position Summary

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!

As a Senior Engineer GPU Graphics Core Performance Verification Engineer, you will help lead pre-silicon performance verification and correlation for Samsung’s next-generation GPU and system-level IP. Your work will directly influence architectural validation, performance predictability, and workload optimization by ensuring GPU designs meet targeted performance expectations across architectural models, emulation, and silicon environments.

In this high-impact individual contributor role, you will contribute to performance verification strategy, develop scalable test infrastructure, and analyze GPU performance behavior across complex graphics and compute workloads. You will partner closely with GPU architecture, modeling, RTL, and validation teams to identify bottlenecks, debug performance issues, and guide performance tuning from early architectural exploration through silicon bring-up.

• Leveraging your expertise in GPU architecture and performance analysis, you architect and drive pre-silicon performance verification strategies, methodologies, and execution flows for graphics core and GPU subsystem validation.
• You develop and maintain performance verification infrastructure, including test environments, workloads, profiling tools, automation, and scalable verification flows to characterize GPU performance across simulation, emulation, and architectural platforms.
• You ensure technical excellence by analyzing, correlating, and comparing performance behavior across architectural models, RTL, emulation, and silicon, identifying bottlenecks and driving data‑driven optimization strategies.
• You lead cross-functional collaboration with GPU architecture, Modeling, RTL, Verification, and Software teams to define performance targets, debug performance issues, align workload behavior with architectural intent, and improve overall GPU efficiency and scalability.
• You inspire high performance by mentoring engineers, advancing performance verification methodologies, and fostering a culture of ownership, innovation, and continuous learning while staying ahead of emerging GPU architectures, graphics workloads, and AI/ML compute trends.

• 2+ years of experience with a Bachelor's degree in Computer Science, Computer Engineering, or relevant technical field, or a Master's degree.
• Strong experience in GPU performance verification, architectural validation, workload analysis, or performance modeling for GPU, CPU, or complex SoC designs.
• Strong understanding of GPU architecture, graphics pipelines, compute workloads, and microarchitecture performance behavior.
• Strong hands‑on programming experience in C++ and Python within Linux development environments.
• Experience developing performance tests, profiling infrastructure, automation frameworks, and workload characterization methodologies.
• Strong experience analyzing and correlating performance behavior across architectural models, RTL simulation, emulation, and/or silicon environments.
• Familiarity with graphics and compute APIs such as OpenGL, Vulkan, OpenCL, or related GPU software stacks.
• Excellent analytical and problem‑solving skills, with the ability to identify bottlenecks, propose solutions and guide teams through implementation.
• Excellent communication and collaboration skills, with the ability to navigate ambiguity and influence in a fast‑paced, global team environment.

• Experience with SystemC, performance simulators, or cycle‑approximate GPU modeling environments.
• Experience with RTL verification, emulation, or post‑silicon performance analysis.
• Familiarity with AI/ML, graphics rendering,…