Senior Performance Engineer

Samsung Semiconductor Inc.; San Jose (CA); On-site; USD 138,000 - 206,000; Full time

Job summary

Samsung Semiconductor Inc. is seeking a Senior LLM Systems Performance Engineer in San Jose, CA. This role involves building AI environments, analyzing system bottlenecks, and supporting co-design decisions for advanced AI platforms.

Ideal candidates will have an MS or PhD in a relevant field and over 5 years of experience in performance engineering. The role requires strong analytical skills and hands-on experience with NVIDIA GPUs and AI workloads.

The position offers a competitive salary range of $138,000 – $206,000 USD and aligns with a flexible work policy.

Qualifications

• 5+ years of experience in performance engineering, AI systems, or high-performance computing.
• Strong understanding of LLM inference and training systems.
• Experience with large-scale distributed AI workloads.

Responsibilities

• Build and operate representative AI environments.
• Collect workload traces and performance data from real-world AI applications.
• Analyze runtime and memory impact on application performance.
• Collaborate with teams to drive performance analysis for AI platforms.

Skills

Performance engineering

AI systems

Distributed systems

High-performance computing

Python

C++

Education

MS or PhD in Computer Science, Computer Engineering or Electrical Engineering

Tools

NVIDIA GPU architecture

Nsight Systems

Nsight Compute

PyTorch

vLLM

TensorRT-LLM

Job description

Senior LLM Systems Performance Engineer

The AGI Computing Lab’s STG group is looking for a Senior LLM Systems Performance Engineer to build representative AI environments, characterize emerging workloads, and drive performance analysis for next‑generation AI platforms. You will work closely with hardware architects, systems engineers, and software researchers to analyze system bottlenecks across compute, memory, communication, and scheduling resources and to support hardware‑software co‑design decisions.

Location: Daily onsite presence at our San Jose, CA office (U.S. headquarters). The position aligns with our Flexible Work policy.

What You’ll Do

• Build and operate representative AI environments, including agentic workflows, distributed inference systems, disaggregated serving architectures, and MoE deployments.
• Collect workload traces, telemetry, and performance data from real‑world AI applications; characterize workload behavior and develop representative benchmarks.
• Analyze the impact of runtime, memory hierarchy, interconnect, and accelerator architecture on application performance across the full hardware and software stack.
• Collaborate with hardware and software teams to drive performance analysis, architecture exploration, and co‑design for next‑generation AI platforms.

What You Bring

• MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
• 5+ years of experience in performance engineering, AI systems, distributed systems, or high‑performance computing, or comparable MS level experience.
• Strong understanding of LLM inference and training systems and NVIDIA GPU architecture.
• Hands‑on experience profiling and optimizing AI workloads on NVIDIA GPU platforms using tools such as Nsight Systems and Nsight Compute.
• Experience with large‑scale distributed AI workloads and modern AI frameworks (e.g., PyTorch, vLLM, TensorRT‑LLM).
• Proficiency in Python and C++.
• Strong analytical and problem‑solving skills.

Base Pay Range: $138,000 – $206,000 USD

Equal Opportunity Employment Policy

Samsung Semiconductor is an equal opportunity employer. We are committed to fostering an environment where all individuals feel valued and empowered to excel, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status.

All candidates will receive adjustments for disability, long‑term conditions, neurodivergence, or pregnancy‑related support, and we guide applicants on how to request accommodations.