Senior Performance Engineer

Please Note:

To provide the best candidate experience amidst our high application volumes each candidate is limited to 10 applications across all open jobs within a 6-month period.

Advancing the Worlds Technology Together

Our technology solutions power the tools you use every day--including smartphones electric vehicles hyperscale data centers IoT devices and so much more. Here youll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of whats possible and powering the future.

We believe innovation and growth are driven by an inclusive culture and a diverse workforce. Were dedicated to empowering people to be their true selves. Together were building a better tomorrow for our employees customers partners and communities.

This role is offered by the STG group within the AGI Lab as part of DSRA. We are a systems research and engineering team working at the intersection of large language models accelerator hardware and high-performance software. Our mission is to design prototype and optimize next-generation AI systems through tight hardwaresoftware co-design. Our team works hands-on with cutting-edge accelerator hardware advanced memory systems and large-scale distributed AI infrastructure. We develop and optimize the software stack required to maximize performance efficiency and scalability for modern and emerging LLM workloads.

We are seeking a Senior LLM Systems Performance Engineer to build representative AI environments characterize emerging workloads and drive performance analysis for next-generation AI this role you will set up and operate realistic LLM serving and agentic AI environments collect workload traces and performance data and develop methodologies to characterize workload behavior. You will analyze system bottlenecks across compute memory communication and scheduling resources and evaluate how emerging workloads interact with AI accelerator architectures and system infrastructure. The ideal candidate combines hands-on experience building large-scale AI systems with strong performance engineering skills and a solid understanding of AI accelerator architecture. You should be comfortable working across the full stackfrom application frameworks and serving systems to runtime software networking memory systems and accelerator will work closely with hardware architects systems engineers and software researchers to understand the performance implications of emerging workloads such as agentic AI long-context reasoning disaggregated inference and Mixture-of-Experts models. Your analysis will help shape future hardwaresoftware co-design decisions and guide the development of next-generation AI infrastructure.

Location: Daily onsite presence at our San Jose CA office / U.S. headquarters in alignment with our Flexible Work policy.

What Youll 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 develop representative benchmarks and identify performance bottlenecks across compute memory communication and scheduling resources.
• Evaluate AI systems across the full hardware and software stack and analyze the impact of runtime memory hierarchy interconnect and accelerator architecture on application performance.
• Collaborate with hardware and software teams to drive performance analysis architecture exploration and hardwaresoftware co-design for next-generation AI platforms.

What You Bring

• MS or PhD in Computer Science Computer Engineering Electrical Engineering or a related field.
• B.S with 5 years of experience in performance engineering AI systems distributed systems high-performance computing or a related in Computer/Electrical Engineering or Computer Science with 3 years of relevant working experience or PhD and 0 years of relevant working experience preferred.
• Strong understanding of LLM inference and training systems.
• Strong understanding of NVIDIA GPU architecture and performance characteristics including compute memory hierarchy communication and system-level bottlenecks.
• Hands-on experience profiling and optimizing AI workloads on NVIDIA GPU platforms using tools such as Nsight Systems Nsight Compute and related performance analysis frameworks.
• Experience analyzing performance of large-scale distributed AI workloads.
• Proficiency in Python and C.
• Experience with one or more modern AI frameworks or serving systems such as PyTorch vLLM SGLang TensorRT-LLM DeepSpeed Ray or Megatron-LM.
• Strong analytical and problem-solving skills.

#LI-VL1

Equal Opportunity Employment Policy

Samsung Semiconductor takes pride in being an equal opportunity workplace dedicated 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.

When selecting team members we prioritize talent and qualities such as humility kindness and dedication. We extend comprehensive accommodations throughout our recruiting processes for candidates with disabilities long-term conditions neurodivergent individuals or those requiring pregnancy-related support. All candidates scheduled for an interview will receive guidance on requesting accommodations.

Our Commitment to Innovation and Fairness

At Samsung Semiconductor we use Artificial Intelligence (AI) tools in the recruitment process to enhance efficiency. However AI is used as a support tool not a final decision-maker. All hiring decisions are made by our human recruiting team and hiring managers to ensure every candidate is evaluated fairly and holistically.

Recruiting Agency Policy

We do not accept unsolicited resumes. Only authorized recruitment agencies that have a current and valid agreement with Samsung Semiconductor Inc. are permitted to submit resumes for any job openings.

Applicant AI Use Policy

At Samsung Semiconductor we support innovation and technology. However to ensure a fair and authentic assessment we ask that candidates rely on their own knowledge and skills throughout the process. AI tools may be used for basic preparation grammar and research but should not be used to generate or assist with submitted content or live interview responses. If we determine that AI is being used outside these guidelines we reserve the right to pause or end the interview and your candidacy may be disqualified.

Trade Secret Notice

By submitting an application you agree not to disclose to Samsungor encourage Samsung to useany confidential or proprietary information (including trade secrets) belonging to a current or former employer or other entity.

Applicant Privacy Policy
Experience:

Senior IC