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The AGI (Artificial General Intelligence) Computing Lab is dedicated to solving the complex system-level challenges posed by the growing demands of future AI/ML workloads. Our team is committed to designing and developing scalable platforms that can effectively handle the computational and memory requirements of these workloads while minimizing energy consumption and maximizing performance. To achieve this goal, we collaborate closely with both hardware and software engineers to identify and address the unique challenges posed by AI/ML workloads and to explore new computing abstractions that can provide a better balance between the hardware and software components of our systems. Additionally, we continuously conduct research and development in emerging technologies and trends across memory, computing, interconnect, and AI/ML, ensuring that our platforms are always equipped to handle the most demanding workloads of the future. By working together as a dedicated and passionate team, we aim to revolutionize the way AI/ML applications are deployed and executed, ultimately contributing to the advancement of AGI in an affordable and sustainable manner. Join us in our passion to shape the future of computing!

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 hardware–software 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 platforms. In 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 stack—from application frameworks and serving systems to runtime software, networking, memory systems, and accelerator hardware. You 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 hardware–software 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 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, 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 hardware–software 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 area. MS 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

What We Offer
The pay range below is for all roles at this level across all US locations and functions. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. We also offer incentive opportunities that reward employees based on individual and company performance.

This is in addition to our diverse package of benefits centered around the wellbeing of our employees and their loved ones. In addition to the usual Medical/Dental/Vision/401k, our inclusive rewards plan empowers our people to care for their whole selves. An investment in your future is an investment in ours.

Give Back With a charitable giving match and frequent opportunities to get involved, we take an active role in supporting the community.
Enjoy Time Away You’ll start with 4+ weeks of paid time off a year, plus holidays and sick leave, to rest and recharge.
Care for Family Whatever family means to you, we want to support you along the way—including a stipend for fertility care or adoption, medical travel support, and virtual vet care for your fur babies.
Prioritize Emotional Wellness With on-demand apps and free confidential therapy sessions, you’ll have support no matter where you are.
Stay Fit Eating well and being active are important parts of a healthy life. Our onsite Café and gym, plus virtual classes, make it easier.
Embrace Flexibility Benefits are best when you have the space to use them. That’s why we facilitate a flexible environment so you can find the right balance for you.

Base Pay Range

$138,000—$206,000 USD

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 Samsung—or encourage Samsung to use—any confidential or proprietary information (including trade secrets) belonging to a current or former employer or other entity.

Applicant Privacy Policy
https://semiconductor.samsung.com/about-us/careers/us/privacy/

Base Pay Range 138000 - 206000 USD

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