Top Tech Jobs & Startup Jobs in Singapore

Internship focused on semiconductor process integration, device reliability, and data-driven improvement for NAND, DRAM, and HBM manufacturing. The intern will study process interactions, failure mechanisms, yield, reliability, and manufacturing data while gaining exposure to analytics, automation, dashboards, and AI/ML tools. Deliverables include technical documentation, analysis reports, improvement evaluations, and an analytics or automation demonstration. The role involves collaboration across process, manufacturing, yield, product, and failure analysis teams.

Lead engineering and maintenance works for Smart Fac and Control systems, implement automation projects, and oversee preventive and corrective maintenance activities.

Own end-to-end performance and power readiness for Data Center SSD programs, perform deep performance analysis and root-cause debug, coordinate cross-functional mitigations, plan test infrastructure, integrate AI-assisted tools, and drive process and continuous improvement to meet program goals.

Lead end-to-end HBM/DRAM component validation: execute time-bound validation runs, develop ATE test programs, perform Verilog simulations and power/thermal characterization, build automation and dashboards, drive silicon debug with cross-functional teams, optimize cycle time, and mentor junior engineers.

Lead data engineering and process-mining initiatives to capture Digital Footprints, generate actionable visualizations and AI-driven optimizations, standardize scalable digital processes across Front-End sites, and track productivity and labor-hour savings via dashboards and cross-functional execution.

As a Realtime Defect Analysis Technology Development Engineer, you will use defect detection equipment, data analysis, and collaborate with engineers to solve process issues and improve efficiency in technology development.

Perform data-driven yield analysis and root-cause debugging across frontend, backend, and test for DRAM products. Conduct electrical characterization and failure analysis to localize defects, collaborate with process, test, and quality teams to implement manufacturing fixes, and apply automation and AI-assisted tools to improve yield and engineering efficiency across NPI to high-volume production.

The role involves yield data analysis in semiconductor manufacturing, resolving yield issues, and collaborating across teams to improve processes.

Lead global initiatives to identify and eliminate high-risk manual touchpoints across Assembly & Test sites by driving automation, robotics, predictive quality and AI-enabled solutions. Conduct onsite validations, redesign end-to-end workflows, establish KPIs and scorecards, and govern program deployment to scale proven solutions across global manufacturing sites while partnering with cross-functional teams to improve product quality and reduce operational errors.

The FE Central Quality Process Engineer will lead new product quality risk assessments and deploy quality control systems while supporting improvements in semiconductor manufacturing processes.