Top Tech Jobs & Startup Jobs in Singapore

Supports NAND product development from silicon through system integration. Responsibilities include translating business and SSD requirements into qualification specifications, developing AI-enabled data workflows, coordinating technology, design, fabrication, assembly, test, quality, supply chain, and business teams, and managing product qualification priorities. The role leads reviews, cross-functional meetings, capability assessments, and resolution of NAND-system issues to enable timely customer product qualification.

Leads NAND product engineering and development, translating business and SSD requirements into qualification specifications. Builds AI-enabled workflows for data extraction, analysis, and program management. Coordinates NAND integration with technology, design, fabrication, assembly, testing, quality, supply chain, and business teams. Represents engineering in reviews, leads cross-functional meetings, organizes capability reviews, and resolves complex NAND-system issues to support timely product qualification and customer delivery.

Supports deployment, maintenance, and sustainment of Micron’s process control systems. Executes system change requests across SPC, FDC, recipe management, specifications, MES, shop-floor systems, and manufacturing applications while ensuring accurate updates, data integrity, and compliant execution.

Lead validation development for High Bandwidth Memory components as a subject matter expert. Develop, maintain, debug, and optimize C/C++ and Python test programs on ATE platforms; improve test stability, repeatability, test time, and parallelism. Own equipment qualification, hardware readiness, platform health, capacity forecasting, and validation infrastructure. Lead root-cause analysis, high-speed I/O and signal-integrity validation, cross-functional collaboration, technical standards, and mentoring of junior engineers.

Intern will analyze semiconductor backend test processes and equipment performance, evaluate new technologies for high-volume manufacturing, identify yield, quality, reliability, cycle-time, and cost improvements, and apply structured problem-solving, risk assessment, FMEA, data analysis, and responsible AI methods. Deliverables include baseline analyses, performance trend findings, qualification summaries, recommendations, technical reports, presentations, and potentially an AI-enabled proof of concept.

Lead global procurement and category strategies for semiconductor capital equipment. Responsibilities include complex commercial negotiations, supplier segmentation and governance, supply assurance, capacity planning, cost optimization, supplier performance improvement, and executive relationship management. The role also applies AI-powered tools, predictive analytics, automation, and business intelligence to improve sourcing efficiency, identify risks, and support strategic decisions across Micron’s technology development and manufacturing roadmap.

Develop a centralized Power BI Enterprise Metrics Hub integrating data from multiple reporting platforms. Responsibilities include defining KPIs, designing an enterprise data model, building interactive dashboards, automating refreshes, analyzing process-control and operational metrics, generating AI-enabled insights, and presenting recommendations. The intern will collaborate with engineering, manufacturing, quality, and analytics stakeholders while producing documentation and knowledge-transfer materials.

Identifies and resolves semiconductor process and equipment issues; leads equipment qualification, process optimization, yield improvement, cost reduction, and new process validation. Manages supplier quality and audits, supports manufacturing controls, and maintains MES databases. Analyzes process data, identifies improvement opportunities, collaborates cross-functionally, and applies statistical methods, automation, and AI-enabled tools in manufacturing operations.

Analyze semiconductor manufacturing signals, process parameters, and test results using Python, SQL, statistics, visualization, and AI-enabled methods. Identify sources of variability, yield loss, and product rejects; develop analytical models and data-driven recommendations for process stability and quality improvement. Document findings, prepare technical reports and presentations, and collaborate with cross-functional engineering stakeholders during a five-month full-time internship.

Develop a prototype AI-enabled equipment health monitoring and reliability analytics framework. Analyze alarms, downtime, maintenance, and performance data; create health indicators; apply statistical and machine learning methods for anomaly detection and degradation analysis; build an intelligent monitoring agent and interactive dashboard; and document and present findings to engineering stakeholders.