Fellow, EPYC AI Product Architecture

Advanced Micro Devices, Inc•Austin, TX

9d•Hybrid

About The Position

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. AMD is seeking a Fellow of EPYC AI Product Architecture to lead the definition of next-generation CPU and platform innovations tailored for AI workloads. You will be a key technical leader within the EPYC AI Product organization, shaping AMD’s AI platform strategy across silicon, systems, and software. This role sits at the intersection of architecture, product definition, customer engagement, and business impact, driving differentiated solutions across cloud, enterprise, and hyperscale deployments. You will collaborate with world-class engineers, technologists, and customers to deliver high-performance, efficient, and scalable platforms for deep learning, generative AI, recommendation systems, and classical ML. You will engage deeply with AMD’s silicon, platform, and software teams to translate workload insights into architectural innovations and platform capabilities that shape the future of AI compute. THE PERSON We are looking for a visionary, results-driven technical leader with a deep understanding of AI workload requirements and system-level architecture. You combine technical breadth across CPUs, servers, and AI acceleration platforms with customer fluency and strategic business insight. You are equally comfortable engaging in low-level performance modeling as you are briefing customers, analysts, and press on AMD’s roadmap and product direction. Key Attributes: Deep technical expertise in CPU and server architecture for AI workloads Proven track record influencing AI platform design at the pod, rack, or datacenter scale Strong understanding of AI software ecosystems, frameworks, and optimization flows Data-driven mindset, with ability to analyze and forecast workload performance across complex systems Exceptional communicator who can translate technical complexity into compelling product narratives

Requirements

Deep technical expertise in CPU and server architecture for AI workloads
Proven track record influencing AI platform design at the pod, rack, or datacenter scale
Strong understanding of AI software ecosystems, frameworks, and optimization flows
Data-driven mindset, with ability to analyze and forecast workload performance across complex systems
Exceptional communicator who can translate technical complexity into compelling product narratives
Several years in high-performance CPU, server, or AI platform architecture, ideally with customer-facing responsibilities
Expertise in AI system deployments at scale (cloud, enterprise, HPC, or edge)
Demonstrated thought leadership in Generative AI (LLMs), vision, or recommender systems
Hands-on experience with performance tools, roofline models, and system simulation
Familiarity with AI compilers, quantization flows (QAT/PTQ), and workload optimization techniques
Proficient in deep learning frameworks such as PyTorch, TensorFlow, and inference runtimes like ONNX Runtime or TensorRT
Understanding of model deployment pipelines, sparsity techniques, advanced numeric formats, and mixed precision
Track record of cross-functional leadership and working in fast-paced, ambiguous environments
MS or PhD in Computer Engineering, Computer Science, Electrical Engineering, or a related field
Recognized industry or academic thought leader; publications and patents in AI architecture a strong plus

Nice To Haves

Optional: CUDA programming or Hugging Face pipelines

Responsibilities

Lead architecture definition for AMD EPYC CPU and server platforms optimized for AI training and inference
Engage with hyperscalers, OEMs, and AI ISVs to align platform features with evolving workload needs
Evaluate and drive new CPU and platform features for deep learning models, including generative AI, vision, and recommender systems
Analyze performance bottlenecks using architecture simulation and hardware instrumentation; propose workload-driven improvements
Drive architectural trade-off analyses across compute, memory, I/O, and network subsystems
Build and refine performance models, automation tools, and workload testbeds for end-to-end analysis
Project and compare performance vs TCO tradeoffs under different system and silicon configurations
Shape AMD’s platform strategy for heterogeneous compute, working closely with GPU and AI accelerator teams
Represent AMD in industry forums, customer briefings, analyst interactions, and press engagements