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Design Architecture, Principal Engineer

Micron Technology

Design Architecture, Principal Engineer

full-timePosted: Aug 10, 2026Updated: Sep 1, 2026Taiwan, Hsinchu

Job Description

Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.HBM Design Architecture — Principal EngineerRole OverviewWe are seeking a highly motivated HBM Design Architecture Engineer (Principal Engineer) to drive exploration and definition of next‑generation AI memory and system environments. In this role, you will analyze emerging infrastructure trends, build performance models, and develop/extend tooling that informs HBM architecture decisions and system‑level trade‑offs.You will work closely with architects and senior engineers across DTPCO, Design, and Product/System teams to translate AI workload requirements into actionable memory subsystem and architectural intercept strategies.Key ResponsibilitiesYou will own and contribute to projects such as:Research and synthesize emerging trends in compute, networking, and storage infrastructure to anticipate how future AI systems will evolve.Lead HBM architecture analysis by defining bandwidth/latency targets, identifying constraints, and translating workload and system data into actionable memory requirements.Develop and maintain simulation frameworks to model AI cluster performance and memory subsystem behavior; validate models against internal and external benchmarks.Build and apply first‑order performance models spanning HBM bandwidth/latency, GPU/CPU interactions, and memory hierarchy trade‑offs to guide architectural decisions.Create and curate trend dashboards using CSP benchmarks and industry datasets; communicate insights, assumptions, and sensitivity analyses to stakeholders.Partner across DTPCO, Design, and Product/System teams to define architectural intercept opportunities, align on requirements, and influence roadmaps for next‑generation AI systems.Required QualificationsBachelor’s or Master’s degree in Electrical Engineering, Materials Science or related field (or equivalent practical experience).Strong understanding of materials and technology challenges spanning hybrid computing systemsExperience with memory subsystem design (HBM, DDR, caches) and how memory behavior impacts AI/ML workloads and system bottlenecks.Strong multi-disciplinary experience in Fab & Foundry space.Preferred SkillsExposure to electrical, materials challenges and advances in microelectronic manufacturing (compute, memory, interconnects).Ability to turn research and model outputs into concise technical recommendations, including trade‑off discussions, risk/unknowns, and roadmap implications. AI Relevant Job Responsibilities: - Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements. - Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work. - Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving businessAbout Micron Technology, Inc.We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all. With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities — from the data center to the intelligent edge and across the client and mobile user experience.To learn more, please visit micron.com/careersAll qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.To request assistance with the application process and/or for reasonable accommodations, please contact at hrsupport_taiwan@micron.com. Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification. Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.

Locations

  • Taiwan, Hsinchu
  • Taiwan, Taichung - Fab 16

Skills Required

  • memory subsystem designintermediate
  • Fab & Foundry spaceintermediate

Required Qualifications

  • Bachelor’s or Master’s degree in Electrical Engineering, Materials Science or related field (or equivalent practical experience). (experience)
  • Strong understanding of materials and technology challenges spanning hybrid computing systems (experience)
  • Experience with memory subsystem design (HBM, DDR, caches) and how memory behavior impacts AI/ML workloads and system bottlenecks. (experience)
  • Strong multi-disciplinary experience in Fab & Foundry space. (experience)

Preferred Qualifications

  • Exposure to electrical, materials challenges and advances in microelectronic manufacturing (compute, memory, interconnects). (experience)
  • Ability to turn research and model outputs into concise technical recommendations, including trade‑off discussions, risk/unknowns, and roadmap implications. AI Relevant Job Responsibilities: - Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements. - Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work. - Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business (experience)

Responsibilities

  • Research and synthesize emerging trends in compute, networking, and storage infrastructure to anticipate how future AI systems will evolve.
  • Lead HBM architecture analysis by defining bandwidth/latency targets, identifying constraints, and translating workload and system data into actionable memory requirements.
  • Develop and maintain simulation frameworks to model AI cluster performance and memory subsystem behavior; validate models against internal and external benchmarks.
  • Build and apply first‑order performance models spanning HBM bandwidth/latency, GPU/CPU interactions, and memory hierarchy trade‑offs to guide architectural decisions.
  • Create and curate trend dashboards using CSP benchmarks and industry datasets; communicate insights, assumptions, and sensitivity analyses to stakeholders.
  • Partner across DTPCO, Design, and Product/System teams to define architectural intercept opportunities, align on requirements, and influence roadmaps for next‑generation AI systems.
  • - Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements.
  • - Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.
  • - Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business

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