Principal System Architect, GPU at Nvidia in Santa Clara, CA

Principal System Architect, GPU Location: US, CA, Santa Clara A key part of NVIDIA's strength is to innovate how we architect and develop our GPU for the changing AI and accelerated workloads. We are constantly looking for ways to improve the scalability of our design, infrastructure and methodology. We are looking for a Principal System Architect with a wealth of experience in shaping and bringing to fruition high-performance, high-volume System-on-Chip (SoC) platforms. The ideal candidate will bring deep technical expertise across multiple SoC domains, along with strong leadership and communication skills. This senior technical position entails hands-on architectural definition and the capability to influence and drive multi-functional engineering teams. What you'll be doing: Define and drive architecture for complex, high-volume GPU products, ensuring they meet our ambitious performance and scalability goals. Perform and guide power and performance evaluation, trade-off assessments, and architectural modeling to identify optimal chip, package and system construction. Lead improvements in architecture, methodology and tools to improve the scalability of our system, collaborating closely with cross-functional engineering teams. Specify and optimize SoC subsystems such as memory architecture, test infrastructure and power management. Collaborate with RTL, verification, physical design, firmware, and software teams to successfully implement and integrate system components. Produce high-quality technical documentation of SoC architecture, specifications, and development trade-offs. Provide technical leadership and mentorship to junior architects and engineers, encouraging a culture of excellence and innovation. What we need to see: Over 15 years in SoC architecture development or similar technical leadership roles. Proven track record of defining and delivering multiple high-volume SoC systems (such as CPU, GPU, modem, networking or similar). Proficiency in evaluating power/performance and architectural modeling in high-level programming languages. Strong understanding of SoC system fundamentals, including memory hierarchy, coherency, clocking, power domains, boot and reset, test, and debug methodologies. Hands-on experience with silicon bring-up, debug and tuning. Excellent interpersonal, leadership, and collaboration skills, with the ability to influence across organizations. Outstanding documentation, written, and verbal communication skills. Master's degree (or equivalent experience) in a relevant subject area: Computer Science, Electrical Engineering or Computer Engineering Ways to stand out from the crowd: Experience with GPU or AI accelerator architecture, including platform aspects, off-chip I/O technologies, and networked multi-GPU systems Knowledgeable in modern packaging technologies, and their costs and benefits Knowledgeable in AI workload characteristics Outstanding analytical and problem-solving skills with a focus on optimizing performance, power, area, and complexity. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until May 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. Additional Locations: US, OR, Hillsboro, US, CA, Remote, US, WA, Redmond