Intern - ID1 ATE PI Engineer
Micron Technology Inc
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. The Process Integration team plays a critical role in developing and manufacturing advanced DRAM technologies that power next-generation computing, data centers, mobile devices, and AI applications. Our team collaborates across Process Engineering, Device Engineering, Yield Engineering, and Technology Development to optimize semiconductor manufacturing processes, improve product performance, and accelerate the successful deployment of leading-edge memory solutions. Through data-driven decision making, innovation, and continuous improvement, we enable the development of technologies that support the future of artificial intelligence and advanced computing.
Position Overview
Micron is seeking a highly motivated Process Integration Engineer Intern for a 6-month internship supporting advanced DRAM technology development and manufacturing. This position provides hands-on experience in semiconductor process integration, electrical and inline data analysis, yield improvement, and cross-functional engineering collaboration. The intern will work closely with experienced engineers to analyze complex manufacturing data, identify process optimization opportunities, and support engineering solutions that enhance technology performance, manufacturing readiness, and AI-enabled innovation.Responsibilities
- Support the integration and optimization of semiconductor process modules across the DRAM manufacturing flow.
- Analyze electrical, inline, process, and yield data to identify performance gaps, yield detractors, and process anomalies.
- Apply statistical analysis and engineering problem-solving methodologies to investigate complex technical issues.
- Partner with Process Integration, Process Engineering, Yield Engineering, Device Engineering, Technology Development, and other cross-functional teams to drive continuous improvement initiatives.
- Utilize data analytics, visualization tools, automation, and AI-assisted technologies to improve engineering efficiency, productivity, and decision-making.
- Support experiments and data analysis to understand relationships between process conditions, device performance, and product yield.
- Develop dashboards, analytical methods, and reporting tools that improve engineering effectiveness and business insights.
- Document technical findings and communicate results, recommendations, and project updates to engineering teams and leadership while leveraging AI in day-to-day activities and tasks.
Minimum Qualifications
- Currently pursuing a Bachelor’s, Master’s, or Ph.D. degree in Electrical Engineering, Materials Science and Engineering, Chemical Engineering, Physics, or a related technical field.
- Strong analytical, critical thinking, and technical problem-solving skills.
- Fundamental understanding of semiconductor devices, semiconductor processing, or semiconductor manufacturing principles.
- Experience with statistical data analysis and interpretation of technical data sets.
- Demonstrated ability to analyze data, draw engineering conclusions, and communicate findings effectively in a collaborative team environment.
Preferred Qualifications
- Knowledge of semiconductor fabrication processes and manufacturing flows; DRAM process knowledge is a plus.
- Knowledge of semiconductor devices, including CMOS and/or capacitor fundamentals.
- Experience with statistical methods such as SPC, DOE, correlation analysis, and yield analysis.
- Experience using engineering data analysis and visualization tools such as JMP and Excel.
- Experience with Python, scripting, automation, dashboards, data visualization, AI tools, or previous semiconductor industry, research, laboratory, or process engineering experience is a plus.
- Experience and/or interest in developing Agentic AI workflows into current or future processes.
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