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