Electrical Failure Analysis Engineer New Grad - Yield Enhancement
No salary listed
Entry
Bachelor's, Master's
Boise, ID, USA
In Person
Hardware EngineeringHardware Validation & Testing
About the job
Requirements
- A bachelor's or master's degree in Electrical Engineering, Computer Engineering, Materials Science, Computer Science, Data Science, or Chemical Engineering.
- Ability to apply knowledge of semiconductor devices, process integration, memory architecture, and device operation to analyze electrical failures and yield issues.
- Ability to perform electrical and failure analysis as defined by area skill guidelines.
- Experience conducting advanced data analysis, statistical evaluation, and data visualization to support yield investigations and failure analysis results.
- Proficiency with data analytics, scripting, automation, or programming tools such as Python, SQL, JMP, Power BI, or Tableau, or equivalent tools.
- Ability to leverage artificial intelligence tools, large language models, and automation technologies to improve data processing, engineering productivity, investigation efficiency, and technical reporting.
- Ability to summarize investigation findings, including potential root cause and recommended actions, in a concise and technically sound report.
- Ability to operate lab equipment safely and perform required tasks and basic troubleshooting.
Responsibilities
- Perform electrical and failure analysis in alignment with defined area skill guidelines and summarize findings using clear, data-driven reporting and artificial-intelligence-assisted documentation tools.
- Operate and support lab equipment while adhering to safety guidelines and supporting department and company objectives.
- Drive root cause investigations by correlating electrical test data, failure-analysis results, process information, manufacturing history, and artificial-intelligence-generated insights to identify yield detractors and recommend corrective actions.
- Develop and maintain yield-monitoring methodologies, screening strategies, defect-classification systems, and artificial-intelligence-assisted detection models to improve excursion response and defect-identification accuracy.
- Partner with Design, Process Integration, Product Engineering, Test, Manufacturing, and Data Science teams to resolve yield and reliability issues and drive product-quality improvements.
- Develop, automate, and maintain data-analysis tools, dashboards, reporting systems, and artificial-intelligence-powered workflows to improve investigation efficiency and reduce manual data processing.
- Apply artificial intelligence, machine learning, statistical methods, and advanced analytics techniques to accelerate defect identification, yield trending, anomaly detection, predictive analysis, and root cause determination.
- Leverage generative artificial intelligence and knowledge-management tools to accelerate technical reviews, investigation planning, report generation, and information retrieval.
- Lead technical reviews and communicate investigation results, risks, recommendations, and data-driven insights to cross-functional stakeholders and management.
- Create and maintain technical documentation, best practices, training materials, artificial-intelligence prompt libraries, and knowledge-sharing resources for the organization.
- Evaluate and implement new electrical-characterization, debug methodologies, automation solutions, and artificial-intelligence-enabled failure-analysis techniques to improve problem-solving capability.
- Support new product introduction, qualification activities, and technology transfers by providing yield analysis, failure-investigation expertise, and data-driven risk assessments.
- Identify opportunities for process improvement, cost reduction, cycle-time reduction, and productivity enhancement through automation, artificial-intelligence adoption, and workflow optimization.
- Provide technical mentorship and training to engineers and technicians on semiconductor device operation, failure mechanisms, data analytics, artificial-intelligence-assisted engineering tools, and debug methodologies.
- Champion artificial-intelligence-enabled ways of working by identifying, evaluating, and implementing emerging technologies that improve engineering productivity, technical insight generation, and decision-making.
- Manage and prioritize multiple investigations simultaneously while ensuring timely communication of critical findings and business-impacting issues.
Desired Qualifications
- Experience applying artificial intelligence, machine learning, predictive analytics, or large language models to engineering, failure analysis, manufacturing, or yield-improvement workflows.
- Experience developing automated data-processing pipelines, dashboards, engineering applications, or workflow-automation solutions.
- Experience mentoring or assisting failure-analysis technicians during yield investigations.
- Familiarity with Merlin and Raptor tester platforms, emission tools, MPI probe stations, nanoprobe tools, and associated data-analysis environments.
- Experience maintaining technical knowledge of semiconductor device structure, operation, and failure mechanisms for current and future technologies.
- Demonstrated participation in digital transformation, artificial-intelligence adoption, continuous-improvement initiatives, or cross-functional technical projects.
- Willingness to evaluate emerging artificial-intelligence technologies and drive adoption of innovative engineering solutions that improve team effectiveness and productivity.
About the company
Micron Technology designs and manufactures memory and storage chips, mainly DRAM and NAND flash, used in data centers, PCs, phones, cars and industrial equipment. It is one of only three companies that make HBM, the stacked high-bandwidth memory placed beside processors in AI servers, and it is the largest memory chipmaker based in the United States. Unlike chip designers that outsource production, Micron runs its own fabs and assembly sites in the United States and across Asia. It earns money by selling chips, memory modules and solid-state drives to cloud providers, device makers and distributors. Micron was founded in 1978 and is headquartered in Boise, Idaho.
Company Size
10,001+
Company Stage
IPO
Headquarters
Boise, Idaho
Founded
1978
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Simplify's Take
What believers are saying
- Demand is surging: in September 2026, Micron reported fiscal 2026 revenue of $133.19 billion, up from $37.38 billion.
- Boise is hiring: in August 2026, Micron planned about 3,500 direct jobs at two Idaho fabs opening from 2027.
- Sales are locked in early: by October 2026, most of Micron's 2027 HBM supply was contracted at higher prices.
What critics are saying
- Revenue is concentrated: about half of Micron's sales came from its top ten customers in each of three years.
- Departing engineers face scrutiny: in September 2026, Micron sued rival YMTC for hiring away at least 20 engineers.
- Boise is feeling the strain: an August 2026 report found the $50 billion Idaho buildout straining local infrastructure.
What makes Micron Technology unique
- AI memory is a three-player club: only Micron, SK hynix and Samsung make HBM, the stacked memory inside AI servers.
- It owns its factories: Micron makes chips in Taiwan, Singapore, Japan, the U.S., Malaysia, China and India.
- Data centers drive the business: its two data center units made $34.28 billion of quarterly revenue reported September 2026.
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Benefits
- Health Insurance
- Dental Insurance
- Vision Insurance
- Disability Insurance
- Parental Leave
- Unlimited Paid Time Off
- Paid Holidays
- Flexible Work Hours