Responsibilities
THE TEAM
AMD's Data Center GPU organization is transforming the AI and HPC landscape. Our mission is to design and market exceptional products—anchored by our Instinct™ GPU portfolio—that power the next generation of computing in enterprise data centers, cloud, and supercomputing environments. If you’re excited by AI disruption and want to be part of building something big, join us.
THE ROLE
AMD is seeking a highly accomplished Principal Modeling Architect to join the Product Architecture and Workload Strategy team for Data Center GPU. This role will be responsible for 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.
You will drive deep analysis of emerging AI/ML, HPC, and data analytics workloads, translating insights into actionable architectural requirements and performance projections. Your work will directly influence silicon, system, and software design, ensuring AMD platforms are optimized for current and future workload trends.
KEY REPSONSIBILITIES
Workload Modeling Leadership
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.
REQUIRED QUALIFICATIONS
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.
Advanced degree in Computer Science, Electrical Engineering, or related field preferred.
PREFERRED QUALIFICATIONS
- 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.
- This role is not eligible for visa sponsorship.
- LOCATION: Bay Area or Remote
Qualifications
