Staff/Senior Engineer -Package Health System and Analytics

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE. LTD.; Singapore; On-site; SGD 80,000 - 140,000; Full time

Job summary

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE. LTD. seeks a Package Health Analyst to advance monitoring and analytics for robust packaging solutions in Singapore.

The role involves hands-on DFT, data analysis, and reliability testing to ensure quality across wafer, assembly, and test stages. The candidate will define metrics, develop AI-enabled dashboards, and collaborate with process and equipment teams. A background in electrical engineering or materials science with 3+ years in semiconductors is

Qualifications

• Bachelor’s or Master’s in Electrical Engineering, Materials Science, or related field.
• 3+ years in the semiconductor industry (packaging/test/reliability).
• Strong data analytics and statistical modeling.
• Proficient in Python and R for data analysis and visualization.
• Experience with AI/ML tools or statistical modeling.
• Knowledge of semiconductor packaging processes and materials.
• Able to work cross-functionally with process, equipment, and reliability teams.
• Familiar with defect inspection systems and inline metrology.
• Aware of advanced packaging technologies (HBM, 2.5D/3D stacking).
• Strong problem-solving and documentation skills.
• Digital fluency and AI literacy for responsible AI tool use.

Responsibilities

• Package Health Metrics & Monitoring: define quantitative health metrics.
• Develop detection mechanisms and dashboards for health assessment.
• Characterize packages electrically and mechanically.
• Inline Defect Characterization: real-time defect detection and classification.
• Next-level characterization for critical defects and predictive modeling.
• Analytics & Knowledge Base: study correlations and build NPI knowledge base.
• End-to-End Traceability: establish traceability across wafer, assembly, test; link process parameters, signals, and defect signatures.
• AI Responsibilities: integrate AI-assisted tools to improve efficiency and share enhancements.

Skills

Data analytics

Statistical modeling

AI/ML tools

Cross-functional collaboration

Documentation

Digital literacy

Problem solving

Education

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

Tools

Python

R

Job description

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 orMaster’s degree in Electrical Engineering, Materials Science, or relatedfield.

• 3+ years of experience insemiconductor 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 packagingprocess, materialinteractionand 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