Nvidia Principal System Architect GPU 

United States, Texas 

66824773

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.