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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.
AMD's AECG group is looking for a GPU Embedded AI/ML Technical Marketing Engineer who can drive end-to-end ROCm enablement for iGPUs on embedded x86 platforms. This role centers on planning, cross-functional alignment, and integrating multiple software components into cohesive, production-ready solutions for embedded markets.
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.
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.