Engineer New Grad - Edge Systems Architecture

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. ## Responsibilities - Gain exposure to Memory and Storage system architecture for Mobile and Client platforms, understanding how workload and architectural choices influence performance, power, and system efficiency. - Support engineering reporting and technical insight generation through result analysis, validation, documentation, and consistent, traceable workload data. - Engage with multi-functional and global collaborators, participate in technical discussions, and help translate requirements and ideas into MCBU workload engineering work. - Support global collaboration across time zones and dynamically represent MCBU workload engineering in collaborator discussions. - Work on Mobile/Client AI workloads and LP5X/LP6 Memory workload characterization, including workload execution, monitoring, gathering data, performance analysis, and comparison of results. - Chip in to benchmarking and system-level analysis across compute, Memory, and Storage to evaluate performance, power, and architectural trade-offs. - Work with AI tooling, automation, workload datasets, and execution infrastructure to support workload processing, analysis, reporting, and engineering efficiency. ## Minimum Qualifications - Bachelor's degree or Master's degree or equivalent experience in Electrical Engineering, Computer Engineering, Computer Science, or a related technical subject area. - Foundational understanding of computer architecture, memory hierarchy, operating systems, and concepts related to overall system efficiency through coursework, projects, internships, or research; understanding or academic exposure to CPU, GPU, NPU/AI accelerators, SoCs, DRAM, NAND, DDR/LPDDR, Memory, and Storage systems. - Exposure to performance benchmarking, workload profiling, data collection, and analysis acquired by engaging in university classes, practical work, internship experiences, or research efforts; programming or scripting experience with Python, C/C++, or similar languages, with an interest in automation and engineering data analysis. - Understanding of AI/ML fundamentals, AI workloads, generative AI, and AI-assisted engineering tools and their application to workload and system analysis; strong analytical and problem-solving fundamentals, with the ability to learn new architectures, tools, and workload methodologies; ability to analyze technical data, document observations, and clearly communicate findings through reports, presentations, and technical discussions. - Ability to work effectively with multi-functional and global engineering teams while dynamically taking ownership as domain knowledge develops. Facilitate coordination across different time zones, which may include meetings outside Boise working hours. ## Preferred Qualifications - Academic, project, internship, or research exposure to Mobile, Client, AI, Memory, Storage, or system performance engineering. - Familiarity with DRAM, NAND, DDR/LPDDR5/5X, PCIe, or NVMe concepts; hands-on exposure to benchmarking, profiling, workload characterization, or performance data analysis. - Exposure to AI/ML workloads, CPU/GPU/NPU computing, generative AI, or AI-assisted engineering tools. - Academic or internship experience with Python/C/C++, scripting, automation, data processing, or visualization; exposure to hardware platforms, embedded systems, SoC development, simulation, or validation environments. - Interest in developing deeper expertise in Memory/Storage architecture, workload engineering, AI workloads, and system-level performance analysis.