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AMD’s Adaptive Embedded Compute Group (AECG) builds products that combine powerful, energy‑efficient CPUs, advanced neural engines, graphics processors, and adaptive embedded compute with programmable logic to deliver Physical AI and edge computing solutions. Across autonomous vehicles and machines, medical and industrial robotics, and other embedded platforms, AMD is no longer building AI solely for insight. We are building safety‑critical and mission‑critical systems in which AI physically interacts with the real world, operating in real time with deterministic behavior and no margin for error. AMD is seeking a Solution Architect – Physical AI to help plan, architect, design, and execute our Physical AI product roadmap. In this role, you will work across silicon, software, and system architecture to enable next‑generation Physical AI platforms and customer solutions
Job Responsibility:
Partner with silicon planning and platform architecture teams to help define silicon features and software stacks for next‑generation Physical AI systems
Collaborate with market segment architects and business leaders to create customer‑focused Physical AI solutions addressing complex requirements across Aerospace, Automotive, Medical, Robotics, Industrial, and Vision markets
Architect heterogeneous AI systems (CPU + GPU + NPU, FPGA)
Work closely with software engineering and product planning teams to define all aspects of the Physical AI software stack, including ROCm and Ryzen™ AI software support for iGPUs and NPUs, AMD’s Virtualized Automotive Stack, Robot Operating System (ROS), Multimedia analytics pipelines, AI models, and Vision‑Language Models (VLMs) and Large Language Models (LLMs)
Evaluate and communicate system‑level tradeoffs and architectural decisions required to deploy AI in real‑time, deterministic, and safety‑constrained environments
Requirements:
Experienced Electrical, Computer, or Systems Engineer with deep experience architecting AI‑enabled systems for robotics, automation, autonomous machines, or other safety‑critical / mission‑critical systems
Hands‑on experience with AI inference hardware (GPU and NPU) and associated software stacks
Experience with robotics application frameworks and system integration
Demonstrated ability to break down large, complex problems into manageable deliverables and to manage and prioritize requirements across multiple stakeholders
BS, MS, or PhD in Computer Science, Computer Engineering, or Electrical Engineering
What we offer:
Benefits offered are described: AMD benefits at a glance