Top Tech Jobs & Startup Jobs in Singapore

Designs and delivers agentic AI systems that transform complex business processes into autonomous, scalable workflows. Responsibilities include process decomposition, AI architecture, agent and tool orchestration, prompt and context strategy, prototyping, security controls, human-in-the-loop design, testing, cross-functional delivery, value measurement, and mentoring. The role requires collaboration with business, architecture, security, platform engineering, and project management teams through production release.

Supports 24x7 advanced semiconductor packaging operations during NPI and early production ramps. Monitors equipment health, SPC/FDC alerts, alarms, process excursions, and operational metrics; performs first-pass troubleshooting and root cause analysis; documents shift events and handovers; supports tool installation, qualification, recovery, and stabilization; and deploys RDA capabilities, dashboards, scripts, and monitoring logic. Collaborates with Process, Equipment, NPI, Automation, IT, and global RDA teams to improve equipment reliability, data integrity, and manufacturing readiness.

Conduct a semiconductor process-engineering project focused on wafer thermal management and plasma strip optimization. Plan experiments and Design of Experiments studies, analyze manufacturing data using statistics, process modeling, visualization, and AI-enabled workflows, and develop predictive analytics linking chuck temperature to process performance. Deliver thermal-characterization findings, optimization recommendations, and a technical presentation aimed at improving process robustness, yield, productivity, and cost performance.

Conduct silicon design validation for advanced NAND products through Verilog simulations, validation planning, laboratory measurements, and data analysis. The intern will use testers, oscilloscopes, probe stations, scripting, and engineering software to analyze validation data, generate technical reports, and prototype AI-enabled workflows for automated data collection, reporting, or anomaly detection.

Supports advanced copper sputter process development for HBM semiconductor metallization. Responsibilities include process characterization, hardware qualification, integration assessment, statistical and machine-learning analysis, defect reduction, yield improvement, and manufacturing readiness. The intern will use AI, manufacturing systems, and data analytics to identify process trends and recommendations while collaborating with process integration, manufacturing, equipment, and quality teams.

Supports a five-month product engineering project involving NAND Flash, memory products, and SSDs. Analyzes test coverage, yield data, electrical measurements, and failure mechanisms; conducts circuit simulations and engineering evaluations; and develops scripts, dashboards, automation, or AI-enabled workflows. The intern documents findings, recommends improvements to product quality and test efficiency, and presents a final technical report under experienced engineering guidance.

Develop an end-to-end analytics and machine learning solution for semiconductor manufacturing data. Analyze electrical, physical, inline, and probe measurements; perform data querying, preprocessing, feature engineering, modeling, optimization, and visualization; and create predictive models and drift-detection methods to improve production-line monitoring and engineering decisions. The intern will document and present findings while collaborating with manufacturing engineering teams.

Intern will analyze semiconductor manufacturing and quality data to detect cell metric drift and potential quality excursions. Responsibilities include statistical analysis, detection modeling, correlation analysis, dashboard and visualization development, AI-enabled data exploration, and technical documentation. The intern will collaborate with engineering teams and deliver a monitoring methodology, analytical report, recommendations, and final presentation.

Supports advanced HBM packaging and new product introduction from development through high-volume manufacturing. Applies engineering, statistical, DOE, FMEA, and control-plan methods; supports low-volume manufacturing, run-at-risk activities, product qualification, technology transfer, and corrective actions. Collaborates with development, manufacturing, and supplier teams globally while using AI-enabled tools, MES, automation, and data analytics to improve efficiency and quality.

Lead HBM package product engineering to improve yield, reduce DPM, and resolve packaging failures via EFA/PFA and cross-functional collaboration. Drive process conversions, test optimization, AI/ML adoption, and project decisions to meet quality, cost, cycle time and scale targets.