TSE KEG Equipment Engineer
Micron Technology
- Location
- Boise, ID - Main Site
- Work model
- On-Site
- Level
- Mid
- H-1B history
- 69 approvals (FY2023)
- Posted
- Sep 1, 2026
About this role
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.
Summary
The Test Solutions Engineering (TSE) organization develops and deploys advanced test solutions that enable high-quality semiconductor manufacturing across Micron’s global network. Within TSE, the Key Equipment Group (KEG) drives innovation, standardization, and operational excellence for wafer probing technologies, test equipment, and probe card solutions. The team partners closely with manufacturing, quality, engineering, and supplier organizations to improve performance, accelerate technology deployment, and deliver scalable manufacturing solutions!
Position
Overview As a TSE KEG Equipment Engineer, you will lead the development, qualification, and deployment of wafer probers, testers, probe cards, and supporting manufacturing technologies. You will collaborate with global cross-functional teams and external suppliers to improve equipment capability, efficiency, reliability, and product quality while enabling next-generation semiconductor technologies. This role offers the opportunity to drive innovation, solve complex technical challenges, and deliver measurable impact across Micron’s worldwide manufacturing operations.
Responsibilities
Lead the development, evaluation, qualification, and deployment of wafer probers, testers, probe cards, and related manufacturing technologies Define equipment specifications, design requirements, and qualification strategies that support global manufacturing and technology roadmaps Drive first-of-a-kind equipment and process introductions, ensuring successful transition from concept through production deployment Lead cross-functional projects with manufacturing, test engineering, process engineering, quality, and supplier partners to achieve business objectives Investigate equipment and process deviations, perform root cause analysis, and implement sustainable corrective actions to improve performance and reliability Design and execute experiments, analyze data, and apply statistical methods to support data-driven decision making and continuous improvement Develop manufacturing metrics, best-known methods (BKMs), and process improvements that enhance quality, yield, throughput, and cost performance Leverage AI-enabled tools and automation solutions to improve engineering productivity, technical problem solving, data analysis, and workflow efficiency Minimum Qualifications Bachelor’s degree in Mechanical Engineering, Electrical Engineering, or a related engineering discipline, or equivalent practical experience 3+ years of experience in equipment engineering, manufacturing engineering, systems integration, or a related technical field Experience leading engineering projects and collaborating with cross-functional teams to deliver technical solutions Experience applying structured problem-solving methodologies, statistical analysis, and Design of Experiments (DOE) techniques Experience using CAD tools, interpreting electrical and mechanical schematics, and supporting equipment development or integration projects Preferred Qualifications Experience supporting semiconductor manufacturing, wafer probe operations, semiconductor test methodologies, or automated manufacturing equipment Experience managing supplier relationships, equipment qualifications, and new technology deployment programs Experience using 3D CAD tools and engineering analysis methods such as thermal, stress, structural, or flow analysis Experience using statistical and data analysis software such as JMP or similar platforms Experience applying AI-enabled tools, workflow automation, or advanced analytics to improve engineering processes and decision making Experience and/or interest in developing Agentic AI