This role pays more than
88%
of similar roles. Most pay
$176,000–$246,150
— the shaded band above.
At the midpoint, this role pays about
$285k
versus about
$211k
for comparable roles.
Based on 240 similar postings.
Employer
About Samsung Semiconductor
Samsung Semiconductor is the global semiconductor business unit of Samsung Electronics, designing and manufacturing memory chips, logic semiconductors, and foundry solutions for a broad range of applications.
Samsung Semiconductor currently has
54 open roles
on FindRole.
Listed pay typically runs
$163,000–$253,000
across 54 roles with salary data.
The Principal Engineer, AI System Architect (Hardware) role at Samsung’s Architecture Research Lab involves leading the architecture team to develop next-generation AI system architectures that address critical bottlenecks in memory capacity and bandwidth. This technical lead will conduct system-level architectural research across compute, memory, and interconnect subsystems, developing analytical and simulation-based frameworks to evaluate AI workloads and identify performance bottlenecks. Key responsibilities include driving design decisions through quantitative modeling and collaborating with cross-functional teams to align theoretical insights with practical implementation. The ideal candidate has a Ph.D. in Computer Science or Electrical Engineering, 15+ years of experience in large-scale computing platforms, expertise in AI system hardware architectures, and proficiency in Python, C++, and PyTorch.
Lead the architecture team in shaping system-architecture strategy and advancing key innovations.
Conduct system-level architectural research for next-generation AI systems, focusing on compute, memory, and interconnects.
Develop analytical and simulation-based frameworks to evaluate AI workloads and identify performance bottlenecks.
Analyze emerging AI models to derive architecture requirements and trade-offs across hardware components.
Drive architecture-level design decisions through quantitative modeling and performance projections.
Perform comparative studies of alternative system architectures, reporting performance metrics for strategic choices.
What we're looking for
Ph.D. in Computer Science, Electrical Engineering, or related field with 15+ years of experience in system architecture for large-scale computing platforms.
Proven hands-on experience developing analytical and simulation models for evaluating AI workloads at the system level.
Deep understanding of AI system hardware architectures including compute, memory hierarchies, and high-performance interconnects.
Strong knowledge of modern AI workloads such as LLMs, DLRMs, and large-scale training systems.
Demonstrated ability to translate workload characteristics into actionable architectural design decisions.
Proficiency in Python, C++, and PyTorch for modeling, analysis, and experimentation.
Excellent communication skills with the ability to influence technical direction across teams.
Python
C++
TensorFlow
PyTorch
GPU
NPU
Windows
Agentic AI
Computer Vision
Audio
Generative AI
Version Control Systems
Agile Project Management
High Performance Computing
Profiling Tools
Software Development Methodologies
Embedded Systems
Computer Architecture