Staff/Senior Engineer -Package Health System and Analytics

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE LTD; Região Norte; Presencial; BRL 120 000 - 180 000; Tempo integral

Resumo da oferta

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE LTD is seeking a Package Health Analyst to advance monitoring, data analysis and reliability testing for advanced packaging solutions. You will define metrics, build dashboards, and apply AI-enabled tools to improve yield and product robustness.

Responsibilities include inline defect characterization, end-to-end traceability across wafer to test, and collaboration with process and equipment teams to translate data into actionable improvements.

Qualificações

• Bachelor’s or Master’s degree in Electrical Engineering, Materials Science, or related field.
• 3+ years of experience in semiconductor industry (complex products preferred), 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

Responsabilidades

• 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.

Conhecimentos

Data analytics

Statistical modeling

Python

R

AI/ML

Cross-functional teamwork

Documentation

Formação académica

Electrical Eng or Materials Science

Ferramentas

Defect inspection systems

Inline metrology

Descrição da oferta de emprego

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