Intern - Product Yield Software Engineer
- Compensation
- Not disclosed
- Location
- Boise, ID - Main Site
- Work setup
- Not specified
- Seniority
- Intern
- Employment
- Internship
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- Pursuing a bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, or a related technical field.
- Experience programming in at least one language such as Perl, Python, C/C++, Java, or similar.
- Strong problem-solving and analytical skills.
- Ability and willingness to learn unfamiliar technologies and engineering concepts.
- Expected graduation date must not be before September 1, 2027.
Nice to have
- Experience with Perl. Familiarity with SQL and relational databases. Experience with Linux/Unix environments.
- Familiarity with web development technologies. Experience working with data visualization or reporting tools. Familiarity with Git or other source-control systems. Exposure to statistics, data science
- Experience using generative AI and AI-assisted development tools to improve engineering productivity.
- Semiconductor knowledge is helpful but not required.
- Ability to work effectively in a diverse, fast-paced engineering environment. Excellent communication skills. Self-motivation, curiosity, and enthusiasm for solving real engineering problems.
Full 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.
As an Intern Product Yield Enhancement (PYE) Software Engineer at Micron Technology, you will help develop software and automation solutions that enable engineers to analyze semiconductor manufacturing and product data more efficiently. PYE engineers work across Research and Development, Manufacturing, Product Engineering, and Global Quality to help take next-generation devices from design to mass production.
In this software-focused role, you will work alongside PYE engineers to develop practical tools that turn large and complex engineering datasets into useful information. Projects may include data processing and visualization, engineering workflow automation, web-based tools, AI-assisted engineering applications, and improvements to existing PYE software systems. This internship is intended to provide a hands-on engineering project where you can apply software development skills to real semiconductor manufacturing problems and see the impact of your work. This is a 3-month internship.
Responsibilities
Your job duties may include:
- Develop and improve software tools used by PYE engineers for engineering analysis and decision-making.
- Create automation for processing, analyzing, and visualizing semiconductor manufacturing and product data. Work with large engineering datasets to identify useful patterns, trends, and relationships.
- Develop scripts, applications, dashboards, reports, or web-based engineering tools.
- Explore practical applications of AI-assisted engineering and software development.
- Improve existing engineering workflows through automation and software integration. Debug, test, document, and maintain software used by engineering teams.
- Collaborate with PYE engineers to understand engineering problems and translate them into effective software solutions.
- Communicate project results and demonstrate completed tools to engineers and management.
- During the internship, you'll have an opportunity to: Build software that engineers can use to solve real manufacturing and product problems. Gain experience working with large-scale semiconductor engineering data. Learn how software, data analytics, and semiconductor engineering come together in a high-volume manufacturing environment. Work directly with experienced engineers and software users. Take ownership of a project from problem definition through implementation and demonstration. Explore how modern AI and automation technologies can improve engineering workflows.