Intern

About the Role

The Realtime Defect Analysis (RDA) Yield Technology team supports advanced DRAM research and development by identifying, analyzing, and reducing manufacturing defects that impact yield and product performance. The team partners closely with engineers across R&D and High Volume Manufacturing to improve process stability, accelerate learning cycles, and drive continuous improvement through data-driven decision making.

As an RDA Yield Technology Intern, you will gain hands-on experience with innovative semiconductor processing, defect inspection systems, and advanced analytical techniques. You will contribute to projects focused on experimentation, defect detection, data analysis, and process optimization while collaborating with multi-functional engineering teams. This role is ideal for individuals who are passionate about problem solving, root-cause investigation, and leveraging technology to improve manufacturing performance.

Key Responsibilities

• Analyze experimental process flows and defect inspection data to identify anomalies, investigate root causes, and support corrective actions.
• Partner with R&D and manufacturing teams to improve yield performance through defect detection, process monitoring, and continuous improvement initiatives.
• Leverage Artificial Intelligence (AI) and data analytics tools to accelerate defect detection, identify yield-impacting trends, automate routine analysis workflows, and generate actionable insights.
• Use inline defect signals, statistical analysis, and Design of Experiments (DOE) methodologies to drive process improvements and earlier detection of manufacturing issues.
• Present technical findings, recommendations, and project results in team meetings and engineering reviews.

Requirements & Tech Stack

• Currently pursuing a Bachelor’s or Master’s degree in Electrical Engineering, Chemical Engineering, Materials Science & Engineering, or a related technical field.
• Demonstrated problem-solving and analytical skills through coursework, research, projects, or internships.
• Fundamental understanding of statistics and experimental analysis methods, including DOE concepts.
• Effective verbal and written English communication skills with the ability to present technical information clearly.
• Ability to work independently and collaboratively in a fast-paced engineering environment.

Preferred Qualifications

• Experience with data analysis, scripting, or programming using tools such as Python, SQL, JMP, or similar platforms.
• Familiarity with semiconductor fabrication processes, defect inspection methodologies, or manufacturing environments.
• Experience applying AI, data analytics, or automation techniques to solve technical or engineering problems.
• Demonstrated ability to investigate process anomalies, perform root-cause analysis, and identify meaningful correlations within complex datasets.
• Proven record of flexibility, initiative, and persistence in achieving project objectives.