Engineer DRAM Product Development Engineer

About the Role

As a Product Development Engineer in the DRAM Technology Node Development group at Micron, you will join a collaborative team building world-class memory technologies. You will work from initial development and silicon bring-up through certification, yield improvement, and production expansion. This opportunity lets you apply your academic background to practical semiconductor engineering skills while working with seasoned engineers on innovative projects.

Key Responsibilities

• Support new DRAM process-node and product development, including build validation, silicon bring-up, qualification, yield learning, and production ramp.
• Analyze electrical test, probe, simulation, and characterization data to determine trends, build marginalities, and potential causes of performance or yield loss.
• Assist with characterization and optimization of memory, logic, and analog functions, such as Sense Amplifiers, timing distribution, calibration, training, and related control circuits.
• Complete experiments and established debug methods; coordinate results, compare outcomes with expectations, and recommend data-supported next steps.
• Collaborate with cross-functional partners to investigate process-, build-, test-, and manufacturing-related issues affecting product quality, robustness, performance, and manufacturability.
• Use approved AI-enabled tools for engineering analysis, coding, automation, visualization, documentation, and problem-solving—while validating outputs and protecting confidential information.

Requirements & Tech Stack

• Bachelor’s degree or master’s degree or equivalent experience in Electrical Engineering, Computer Engineering, Physics focusing on semiconductor electronics, or a related technical area.
• Foundational understanding of semiconductor devices, CMOS circuits, digital or analog electronics, memory operation, computer architecture, build verification, test, or data analysis.
• Demonstrated problem-solving ability through coursework, laboratory work, research, internships, co-ops, or technical projects.
• Build proficiency with approved AI-assisted engineering tools and critically evaluate AI-supported results.
• Ability to collect, coordinate, analyze, and communicate engineering data using tools such as Python, JMP, MATLAB, Excel, or similar software.

Qualifications

• Coursework or project experience in semiconductor device physics, VLSI, CMOS building, analog or digital circuits, memory architecture, statistics, or the composition of experiments.
• Exposure to DRAM or other memory technologies, circuit simulation, Verilog, CAD tools, bench characterization, semiconductor test, probe, or electrical failure analysis.
• Experience developing scripts, dashboards, data pipelines, or automation that improves analysis quality or workflow efficiency.
• Familiarity with structured problem-solving methods, statistical process control, development of experiments, or root-cause analysis.
• Evidence of initiative, curiosity, collaborative behavior, and the ability to learn unfamiliar technical concepts.
• Experience applying AI, machine learning, or generative AI to engineering workflows and decision support.