Top Tech Jobs & Startup Jobs in Singapore

This internship evaluates wet etch process conditions and equipment parameters to reduce manufacturing defects, improve etch-rate uniformity, and increase process stability. Responsibilities include analyzing process data, conducting characterization studies, evaluating recipes and equipment settings, developing qualification plans, and making engineering recommendations. The intern will gain experience in semiconductor manufacturing, experimental design, process engineering, technical communication, and AI-enabled data analysis.

Own NAND Failure Investigation activities for product qualification and sustaining support. Debug NAND, firmware, controller, signal integrity, and media management issues using logs, characterization data, protocol traces, tester data, and silicon measurements. Lead root-cause analysis, corrective actions, qualification, NPI, manufacturing readiness, and reliability improvements. Collaborate cross-functionally while developing automation and AI-assisted workflows to accelerate debugging and issue resolution.

Develop and deploy advanced semiconductor packaging technologies for high-performance memory products. Drive package integration, yield and quality improvements, cost reduction, process control, data analytics, and manufacturing readiness. Collaborate with process, product, assembly, test, reliability, and quality teams from technology development through high-volume production. Create process and model-of-record documentation and use Python, R, SQL, Visual Basic, and semiconductor control systems to analyze data and improve integration flows.

Five-month internship analyzing semiconductor dry etch process and equipment data to identify variation, performance drift, productivity loss, and yield impacts. The intern will use statistical analysis, Python, SQL, JMP, Excel, dashboards, and AI-enabled methods to correlate manufacturing, metrology, and equipment data, then recommend process, hardware, recipe, or monitoring improvements.

Develop an AI-enabled dashboard for CMP equipment health and wafer breakage risk prediction. Analyze semiconductor manufacturing and equipment datasets, correlate maintenance and process indicators with breakage and yield excursions, build risk-scoring models, and create Power BI visualizations and automated engineering reports. The intern will collaborate with equipment engineers and gain experience in predictive analytics, reliability engineering, statistical analysis, and semiconductor manufacturing.

Develop and optimize wafer-level semiconductor packaging processes, including wafer thinning and backside metal interconnects. Evaluate equipment and materials, establish process parameters, improve quality and yield through SPC, DOE, defect analysis, and advanced controls, and coordinate technology transfers from development through high-volume manufacturing. Collaborate across packaging, wafer fabrication, assembly, product engineering, and quality teams while documenting process and model records. Apply AI-enabled tools to improve analysis, efficiency, and operational outcomes.

Senior Product Engineering role focused on functional and design validation of advanced NAND devices. Responsibilities include developing deterministic and pseudo-random Verilog test programs, automating validation with C, Python, and Perl, analyzing failures, identifying root causes, and driving cross-functional issue resolution. The role also applies AI/ML, data analytics, dashboards, and anomaly detection to improve test coverage, failure triage, debug productivity, and release readiness.

Coordinates process improvements for NAND Flash production, focusing on yield, quality, reliability, and output. Responsibilities include designing and analyzing experiments, investigating yield and quality issues, interpreting complex fab data, optimizing processes, communicating module issues, and leading cross-functional engineering initiatives. The role collaborates with production, process and equipment engineering, industrial engineering, technology development, and global partner teams while using AI-assisted tools to improve efficiency and operational outcomes.

Develop and optimize semiconductor metrology recipes for advanced packaging processes. Establish inspection methods, process monitoring strategies, control plans, SPC charts, and OCAPs. Analyze defect and yield data using statistical tools and dashboards, manage metrology equipment performance, and coordinate technology development with packaging, wafer fabrication, assembly, test, product engineering, and quality teams. The role requires semiconductor process or equipment engineering expertise, hands-on metrology experience, and strong programming and data analytics skills.

Supports the AI Process Intelligence team through Python automation prototypes, AI agent proofs of concept, predictive modeling, data pipelines, system connectors, controlled model testing, and technical documentation. Works under senior engineers and process architects in a structured, non-production environment while learning AI architecture, automation workflows, API integration, Agile development, DevOps, and knowledge integration.