Senior Performance Engineer

Overview Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you’ll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what’s possible and powering the future. We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We’re dedicated to empowering people to be their true selves. Together, we’re building a better tomorrow for our employees, customers, partners, and communities. The AGI (Artificial General Intelligence) Computing Lab is dedicated to solving complex system-level challenges posed by future AI/ML workloads. Our team develops scalable platforms that handle computational and memory requirements while minimizing energy consumption and maximizing performance, collaborating closely with hardware and software engineers to address AI/ML workloads and explore new computing abstractions. 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. 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 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. Benefits Competitive pay range: $138,000 - $206,000 USD. Paid time off: 4+ weeks of PTO each year, plus holidays and sick leave. Family support: stipend for fertility care or adoption, medical travel support, and virtual vet care for pets. Well‑being: on‑demand mental health apps, free confidential therapy sessions. Fitness: onsite café and gym, virtual classes. Flexibility: benefits designed to fit individual needs. 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. Applicant Privacy Policy #J-18808-Ljbffr Conductor