Reliability Lab Engineer — AI-Driven Process & Automation

Micron Technology, Inc.; Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

Micron Technology, Inc. is seeking a Reliability Engineer to own lab processes, qualifications and continuous improvement for semiconductor reliability workflows.

You will lead structured root-cause analyses and implement corrective actions across TC, HAST, HTS, burn-in and CSAM domains. You will work closely with Operations, Quality and Product teams to analyze trends, drive data-driven decisions and identify opportunities for automation, AI-enabled improvements and digitalization to boost

Qualifications

• Bachelor’s or Master’s degree in an engineering field such as mechanical, electrical/electronics, mechatronics, materials, manufacturing or industrial engineering.
• Strong analytical and problem-solving capabilities.
• Experience with semiconductor reliability or backend lab processes is preferred.

Responsibilities

• Own reliability lab processes from qualification to implementation and continuous improvement.
• Lead RCA/5M1E, FMEA, DOE and risk assessment to resolve reliability issues.
• Collaborate with Operations, Quality, Product and other teams to drive data-driven decisions and process improvements.

Skills

Reliability lab processes

Root cause analysis

Data-driven decision making

Automation & AI in processes

Communication skills

Education

Bachelor's/Master's degree in Mechanical, Electrical/Electronics, Mechatronics, Materials, Manufacturing, Industrial Engineering or related engineering field

Tools

Python

SQL

Tableau

Power BI

Power Automate

Job description

Micron Technology, Inc. is seeking a Reliability Engineer to own lab processes, qualifications and continuous improvement for semiconductor reliability workflows.

You will lead structured root-cause analyses and implement corrective actions across TC, HAST, HTS, burn-in and CSAM domains. You will work closely with Operations, Quality and Product teams to analyze trends, drive data-driven decisions and identify opportunities for automation, AI-enabled improvements and digitalization to boost