HBM PYE Product Development Failure Analysis Engineer

Micron Technology•Boise, ID
•Onsite

About The Position

Micron Technology is hiring an HBM Product Yield Enhancement Product Development Failure Analysis Engineer in Boise, Idaho, to help bring next-generation HBM devices from design through qualification and into mass production. As part of the HBM Product Development Failure Analysis team, this role helps ensure product reliability, accelerate time to market, and support production ramp by identifying and resolving component-level failures during new product introduction. The engineer applies electrical, physical, and statistical failure-analysis techniques to characterize failures, identify root causes, and drive corrective actions. The role works with cross-functional engineering teams and uses advanced analytics, statistical methods, and AI-enabled tools to improve failure detection, yield, reliability, and product performance. The position may be entry level for candidates with a master's degree or equivalent experience, or may be filled at the Senior or Staff level.

Requirements

  • Bachelor’s degree in Electrical Engineering, Computer Engineering, Physics, Materials Science, or a related field.
  • At least 2 years of experience performing electrical and statistical failure analysis to identify and understand failure mechanisms.
  • At least 2 years of experience applying electrical and physical characterization techniques for semiconductor failure analysis.
  • Demonstrated analytical and problem-solving skills, including applying statistical methods and tools to data analysis.
  • Experience using AI, machine learning, or data analytics tools to support engineering analysis and root-cause investigations.
  • Coursework, training, or practical experience in one or more of VLSI, semiconductor device physics, semiconductor processing, Python programming, and statistics.
  • Strong written and verbal communication skills and ability to collaborate effectively in multidisciplinary engineering teams.

Nice To Haves

  • At least 7 years of experience performing electrical and statistical failure analysis in the semiconductor industry.
  • At least 7 years of experience applying electrical and physical characterization techniques for semiconductor device and component analysis.
  • Advanced coursework or hands-on experience in VLSI design, semiconductor processes, device physics, Python, and applied statistics.
  • Experience using artificial intelligence or generative AI tools, such as Copilot or Claude, for large-scale data analysis, failure prediction, and root-cause identification.
  • Experience using statistical analysis software such as JMP.
  • Demonstrated ability to influence technical outcomes and drive issue resolution in a multidisciplinary engineering environment.
  • Proven ability to communicate complex technical findings to diverse team members and lead cross-functional collaboration.

Responsibilities

  • Perform electrical, physical, and statistical failure analysis to identify, characterize, and understand defect and failure mechanisms in HBM products.
  • Analyze component- and system-level data to determine failure root causes using statistical techniques, engineering methodologies, and AI-enabled tools.
  • Apply AI tools, such as Copilot and Claude, and improved analytics to enhance failure detection, reliability learning cycles, yield improvement, and component performance.
  • Collaborate with Product, Process, Test, Quality, and Manufacturing Engineering teams to resolve fabrication, assembly, and test-related issues.
  • Identify process defects, assembly-related failures, and test-flow marginalities through detailed data analysis and characterization.
  • Communicate technical findings, recommendations, and corrective actions, and drive issue resolution across multidisciplinary teams.
  • Support rapid production ramp, product qualification, and continuous reliability improvement initiatives.

Benefits

  • Choice of medical, dental, and vision plans.
  • Programs to help protect income in the event of illness or injury.
  • Paid family leave.
  • Paid time off.
  • Paid holidays.
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