This role pays less than
56%
of similar roles. Most pay
$172,000–$246,150
— the shaded band above.
At the midpoint, this role pays about
$208k
versus about
$209k
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.
As a Senior Staff AI System Architect at Samsung’s Architecture Research Lab, you will play a pivotal role in bridging AI workloads with system architecture and hardware design. Your day-to-day responsibilities include developing analytical and simulation-based frameworks to evaluate performance bottlenecks across compute, memory, and interconnect subsystems for next-generation AI systems. You will analyze emerging AI workloads like LLMs and DLRMs to derive architectural requirements and trade-offs, drive quantitative modeling, and perform comparative studies of system architectures. This role requires a Ph.D. in Computer Science or Electrical Engineering with 5+ years of experience in large-scale computing platforms, proficiency in Python, C++, and PyTorch, and strong knowledge of AI system hardware architectures. You will collaborate closely with cross-functional teams to align modeling insights with implementation realities and communicate architectural recommendations through technical presentations.
Conduct system-level architectural research for next-generation AI systems.
Develop and maintain analytical and simulation-based modeling frameworks to evaluate AI workloads.
Analyze emerging AI workloads to derive architecture requirements and trade-offs.
Drive architecture-level design decisions through quantitative modeling and performance projections.
Perform comparative studies of alternative system architectures, reporting key metrics.
What we're looking for
Ph.D. in Computer Science, Electrical Engineering, or related field with 5+ years of experience in system architecture for large-scale computing platforms.
Proven hands-on experience developing analytical and simulation models for AI workload performance evaluation.
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.
Ability to translate modeling results into actionable architectural design decisions.
Proficiency in Python, C++, and PyTorch for modeling, analysis, and experimentation.
Flutter
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Python
Java
AWS
Microservices
Event-driven design
CI/CD
Conversational AI
Recommendation engines
Distributed systems
Kafka
PostgreSQL
Redis
GraphQL
FinTech
Mobile app development