This role pays less than
84%
of similar roles. Most pay
$177,250–$235,750
— the shaded band above.
At the midpoint, this role pays about
$174k
versus about
$206k
for comparable roles.
Based on 240 similar postings.
Employer
About Samsung Electronics
Samsung Electronics is a South Korean multinational corporation and a global leader in technology, specializing in consumer electronics, semiconductors, and home appliances.
Samsung Electronics currently has
94 open roles
on FindRole.
Listed pay typically runs
$106,000–$174,500
across 58 roles with salary data.
Senior Engineer, GPU Graphic Core Performance Verification will join the GPU Architect team to lead pre-silicon performance verification and correlation for next-generation GPU and system-level IP. This individual contributor role involves developing scalable test infrastructure, analyzing performance behavior across complex graphics and compute workloads, and identifying bottlenecks during architectural exploration through silicon bring-up. The candidate will collaborate with architecture, modeling, RTL, and software teams to ensure designs meet performance expectations. Key technical requirements include proficiency in C++ and Python within Linux environments, along with experience in GPU architecture, graphics pipelines, and microarchitecture behavior. Candidates should be familiar with APIs such as OpenGL, Vulkan, or OpenCL. The role focuses on the specific challenge of ensuring performance predictability and optimization for mobile GPUs supporting advanced features like ray tracing and AI/ML compute trends.
Lead pre-silicon performance verification and correlation for next-generation GPU and system-level IP.
Develop and maintain scalable test infrastructure, including profiling tools, automation frameworks, and workload characterization methodologies.
Analyze and correlate performance behavior across architectural models, RTL simulation, emulation, and silicon environments.
Identify hardware bottlenecks and drive data-driven optimization strategies to improve GPU efficiency.
Define performance targets and align workload behavior with architectural intent in collaboration with cross-functional teams.
Develop performance verification strategies and execution flows for graphics core and GPU subsystem validation.
Mentor engineers and advance performance verification methodologies to stay ahead of emerging AI/ML compute trends.
What we're looking for
Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or a Master's degree.
2+ years of experience in GPU performance verification, architectural validation, workload analysis, or performance modeling for GPU, CPU, or SoC designs.
Strong understanding of GPU architecture, graphics pipelines, compute workloads, and microarchitecture performance behavior.
Hands-on programming experience in C++ and Python within Linux development environments.