About The Position

This role will be part of Micron’s DRAM Technology group, where engineers work at the forefront of memory innovation. Our extended team spans global sites and cultures, and we thrive on collaboration, inclusion, and shared learning as we deliver industry leading DRAM products. You will shape the long-term reliability of current and next-generation Dynamic Random-Access Memory (DRAM) technologies used worldwide. In this role, your work directly influences product lifetime predictions, qualification decisions, and technology improvements. You will combine hands-on experimentation, modeling, and data analysis to solve complex reliability challenges. Your insights will help advance industry-leading memory products.

Requirements

  • Bachelor’s degree in electrical engineering, physics, materials science, or a related field, or equivalent practical experience.
  • 5+ years of industry or related experience demonstrating strong engineering depth.
  • Proven analytical and problem-solving skills with the ability to work across multiple engineering disciplines.
  • Clear and effective communication skills for presenting complex technical topics to diverse audiences.

Nice To Haves

  • Experience with modeling approaches such as physics-based, statistical, or machine learning methods.
  • Hands-on experience with semiconductor test equipment, reliability stress systems, or electrical characterization tools.
  • Understanding of complementary metal-oxide-semiconductor (CMOS) process technology and degradation mechanisms.
  • Understanding of digital and analog CMOS circuit operation.
  • Experience with scripting or programming, such as Python, for data analysis and automation.

Responsibilities

  • Design and execute reliability characterization for DRAM products, including stress test definition, simulation, data collection, and failure analysis.
  • Develop reliability models that predict product lifetime under both field-use and accelerated conditions.
  • Apply automation and artificial intelligence–driven approaches to improve reliability prediction methods and workflows.
  • Analyze large-scale reliability datasets to identify degradation trends, failure signatures, and early warning indicators.
  • Partner with design, process, test, and qualification teams to translate reliability insights into actionable improvements.
  • Communicate technical findings clearly through presentations, technical forums, and written reports to support key risk decisions.
  • Contribute to a strong technical culture by sharing knowledge and mentoring peers.

Benefits

  • Choice of medical, dental and vision plans
  • Benefit programs that help protect your income if you are unable to work due to illness or injury
  • Paid family leave
  • Robust paid time-off program
  • Paid holidays
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