Principal Modeling Architect - DC GPU

Advanced Micro Devices, Inc • San Jose, CA

9h • Remote

About The Position

At AMD, the mission is to build products that accelerate next-generation computing experiences across various domains, including AI and data centers. The company fosters a culture of innovation, collaboration, and a shared passion for creating extraordinary solutions. AMD's Data Center GPU organization is dedicated to transforming the AI and HPC landscape by designing and marketing exceptional products, particularly their Instinct™ GPU portfolio, for enterprise data centers, cloud, and supercomputing environments. AMD is seeking a highly accomplished Principal Modeling Architect to join the Product Architecture and Workload Strategy team for Data Center GPU. This role involves leading the development and application of advanced workload modeling methodologies to inform the architecture, design, and optimization of AMD’s next-generation Instinct™ GPU and data center platforms. The architect will conduct deep analysis of emerging AI/ML, HPC, and data analytics workloads, translating insights into actionable architectural requirements and performance projections, directly influencing silicon, system, and software design to ensure optimal performance for current and future workload trends.

Requirements

• 12+ years of experience in workload modeling, performance engineering, system architecture, or related technical domains.
• Demonstrated expertise in modeling and analyzing AI/ML, HPC, or large-scale data analytics workloads on GPU or accelerator platforms.
• Deep understanding of performance modeling methodologies, benchmarking tools, simulation environments, and workload characterization techniques.
• Experience collaborating across hardware, software, and system engineering teams to drive workload-informed architectural decisions.
• Strong analytical, communication, and technical writing skills; ability to synthesize complex data into actionable insights.

Nice To Haves

• Advanced degree in Computer Science, Electrical Engineering, or related field.
• Experience with ROCm, CUDA, or other GPU programming frameworks.
• Familiarity with compiler/runtime systems, kernel libraries, and developer tooling for AI/ML workloads.
• Track record of publishing workload analysis or performance modeling research in peer-reviewed venues.
• Experience engaging with hyperscalers, CSPs, or large enterprise customers on workload deployment and optimization.

Responsibilities

• Develop and refine workload modeling frameworks to characterize and project performance, scalability, and resource utilization for AI/ML, HPC, and data analytics workloads.
• Analyze emerging model architectures (e.g., LLMs, transformer variants, graph neural networks), datatypes, and scaling methodologies to anticipate future platform requirements.
• Collaborate with architecture, silicon design, software, and performance engineering teams to translate workload insights into platform-level technical requirements.
• Lead benchmarking, profiling, and simulation efforts to validate architectural assumptions and guide design trade-offs.
• Produce detailed workload characterization reports, performance projections, and sensitivity analyses to inform platform strategy and technical decision-making.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Number of Employees: 5,001-10,000 employees