About The Position
The HBM Product Yield Enhancement Product Development Failure Analysis (PDFA) Engineer supports new High Bandwidth Memory (HBM) product introductions, focusing on product reliability and component-level failure analysis. The PDFA team helps bring next-generation HBM products from initial design through high-volume manufacturing, working with Product, Process, Quality, and Test Engineering organizations to identify and resolve issues affecting yield, reliability, and product performance. The engineer uses electrical characterization, physical analysis, statistical methodologies, and AI-enabled data analysis tools to identify failure mechanisms and support rapid production ramps. The role calls for strong analytical skills, collaboration across functions, and the ability to turn complex data into actionable engineering solutions.
Requirements
- Bachelor's degree in Electrical Engineering, Computer Engineering, Physics, Materials Science, or a related technical field, or equivalent experience.
- Experience or coursework in semiconductor device physics, semiconductor manufacturing processes, or VLSI design.
- Demonstrated knowledge of statistical analysis techniques and data-driven problem solving.
- Experience using Python or similar programming languages for data analysis and engineering applications.
- Ability to analyze complex technical data and communicate findings effectively in a collaborative engineering environment.
Nice To Haves
- Master's degree in Electrical Engineering, Computer Engineering, Physics, Materials Science, or a related field.
- Academic or industry experience in semiconductor failure analysis, yield enhancement, reliability engineering, or product characterization.
- Experience applying AI, Generative AI, or AI-assisted analytical tools to engineering investigations and data analysis.
- Knowledge of test methodologies, process integration, and advanced memory technologies, including HBM products.
- Experience working with large datasets and applying statistical software or machine learning techniques to identify failure trends and process improvements.
Responsibilities
- Perform electrical, physical, and statistical failure analysis to identify and understand component failure mechanisms.
- Analyze characterization and manufacturing data to determine root causes of fabrication, assembly, and test-related failures.
- Collaborate with Product, Process, Quality, and Test Engineering teams to resolve yield, reliability, and process defect issues.
- Use AI-enabled tools and statistical methods to evaluate large datasets, identify trends, and improve component performance.
- Communicate findings, corrective actions, and risk assessments to cross-functional partners to support product qualification and production ramp.
Benefits
- Medical, dental, and vision plans
- Income protection benefits for illness or injury
- Paid family leave
- Paid time off
- Paid holidays
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
