Staff/Senior Engineer -Package Health System and Analytics

The Package Health Analyst will contribute to the development and execution of package health monitoring, simulation, and characterization activities. This role involves hands-on engineering work in DFT, data analysis, and reliability testing to ensure robust packaging solutions

Key Responsibilities

• Package Health Metrics & Monitoring

• Define quantitative package health metrics

• Develop detection mechanisms and monitoring dashboards for continuous health assessment.

• Perform electrical and mechanical characterization of packages.

• Inline Defect Characterization

• Implement real-time defect detection and classification (critical vs. non-critical).

• Conduct next-level characterization for critical defects and integrate findings into predictive models.

• Advanced Analytics & Knowledge Base

• Perform correlation and causation studies between process variables, defect patterns, and reliability outcomes.

• Build and maintain a structured knowledge base for package health learnings to enable NPI handover and future technodes.

• End-to-End Traceability

• Collaborate with process and equipment engineers to establish traceability across wafer, assembly, and test stages.

• Develop data pipelines and tools for linking process parameters, equipment signals, and defect signatures.
  

• AI Responsibilities
  Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements.
  Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.
  

Qualifications

• Bachelor’s or Master’s degree in Electrical Engineering, Materials Science, or related field.

• 3+ years of experience in semiconductor industry (complex products preferred), preferably in packaging, test, or reliability engineering.

• Strong data analytics and statistical modeling skills. Proficiency in Python/R for data analysis and visualization is a plus

• Experience with AI/ML tools or statistical modeling.

• Strong understanding of semiconductor packaging process, material interaction and properties.

• Ability to work cross-functionally with process, equipment, and reliability teams.

• Knowledge of defect inspection systems and inline metrology.

• Familiarity with advanced packaging technologies (HBM, hybrid bonding, 2.5D/3D stacking).

• Strong problem-solving and documentation skills

• Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business outcomes