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AMD's Adaptive Embedded Compute Group (AECG) builds products that blend powerful, energy-efficient processors, advanced neural engines and graphics processors, and adaptive embedded compute with programable logic to build edge computing solutions. From autonomous vehicles and industrial robotics to smart healthcare devices, AMD AECG is redefining intelligent edge computing.
Job Responsibility:
Customer-Facing Content for Reference Applications: Translate internal reference designs for AMD Embedded APUs into customer-ready technical training and reference designs
Articulate system-level value propositions language that sales and partners can confidently use with Embedded AI customers
Develop 'what to say to customers' guidance, including embedded system deployment, architectural tradeoffs, and design best practices
Sales and Field Enablement: Partner closely with sales, FAEs, and solutions engineers to ensure consistent, accurate, and compelling messaging for AMD embedded x86 AI solutions
Create and maintain enablement assets such as pitch decks, whitepapers, FAQs, competitive positioning, and architectural overviews
Support strategic customer and partner engagements by providing deep technical context and architectural guidance when needed
Technical Training: Design and deliver high-impact technical training for internal audiences (sales and FAEs) covering AMD embedded x86 AI Solutions
Deliver external technical training for ODMs and end customers, tailoring content for varying levels of technical depth
Build modular, reusable training content (slides, diagrams, labs, recordings) that can be scaled globally
Cross-Functional Collaboration: Work closely with technical sales, application teams, product management, and engineering teams to stay aligned with current and future reference designs and roadmap direction
Provide structured feedback from the field to influence future reference architectures, documentation, and software stacks
Ensure technical accuracy, consistency, and quality across all published customer-facing materials
Requirements:
Strong understanding of GPU architectures and GPU software stacks, including graphics, compute, and AI/ML workloads, across Linux and Windows environments
Hands on experience with implementing AI/ML and high performance compute workloads for a variety of applications using GPUs
Experience with virtualization and embedded systems is highly desirable
Confidence in presenting complex technical material to technical sales and customers
Strong cross-functional communication and dependency management skills with attention to detail
Experience in software integration, program planning, or technical project coordination
BS in Computer Science, Computer Engineering, or Electrical Engineering. MS or PhD is a plus
Nice to have:
Experience with virtualization and embedded systems