Top Tech Jobs & Startup Jobs in Singapore

Analyzes semiconductor photo manufacturing data to identify factors affecting train size, throughput, cycle time, tool utilization, and reticle availability. The intern will build predictive or simulation models, dashboards, and recommendations to optimize manufacturing performance and factory output. Responsibilities include collecting and validating data, analyzing historical trends, evaluating optimization scenarios, and presenting findings.

Manage the application lifecycle for software systems supporting highly automated semiconductor manufacturing. Analyze business and technical requirements, develop and maintain software solutions, enforce secure development practices, conduct testing and training, apply updates and patches, monitor systems, prevent downtime, and use AI, automation, and analytics tools to improve delivery and operational efficiency.

Drive dry etch process and equipment performance using advanced data analytics, automation, machine learning, statistical modeling, and generative AI. Lead cross-functional initiatives integrating manufacturing, equipment, process, and business data. Develop scalable analytics solutions to improve productivity, tool utilization, cycle time, excursion response, process control, and manufacturing costs. Collaborate with suppliers and internal digital teams to evaluate and deploy AI technologies for semiconductor manufacturing.

Develop end-to-end data science and digital twin solutions for manufacturing, planning, and supply chain operations. Responsibilities include business problem framing, data analysis, mathematical optimization, discrete event simulation, software and pipeline development, API and UI creation, deployment, user adoption, benchmarking, and continuous improvement across global manufacturing sites.

Own the product backlog and delivery of AI and agentic solutions for procurement and planning. Translate stakeholder needs into requirements, user stories, data requirements, and implementation plans. Collaborate with data scientists and engineers to assess data readiness, develop solutions, and drive products from discovery through deployment, adoption, and value realization. Identify opportunities to improve cost efficiency, productivity, and capital efficiency through AI, automation, and workflow optimization.

Conducts NAND product validation, characterization, bench testing, and electrical failure analysis. The intern analyzes test data, evaluates product changes and failure cases, develops automation scripts, documents methodologies, and presents technical findings. The role provides hands-on exposure to NAND device physics, semiconductor test equipment, product specifications, and engineering problem-solving while collaborating with Product Engineering and cross-functional teams.

Leads complex cross-functional planning initiatives across semiconductor manufacturing, supply chain, engineering, finance, and digital teams. Translates ambiguous business challenges into structured analyses, process improvements, system requirements, and actionable recommendations. Drives program execution, stakeholder alignment, data quality, planning-system enablement, automation, analytics, optimization, change adoption, and sustained benefits. Serves as a subject matter expert and mentors others while improving planning capabilities and decision support.

Participate in functional and design validation of advanced NAND products using silicon and simulation platforms. Develop test cases, automation scripts, and engineering tools; analyze performance, timing, and power characteristics; investigate failures through log review and root-cause analysis; and document findings in technical reports and presentations.

Develop an AI-enabled optimization engine for wafer test movement configurations, using machine learning and optimization techniques. Analyze historical semiconductor data, benchmark recommendations, build a web application for visualization and comparison, and validate improvements in test time and tester utilization. The role involves collaboration with Automation, Equipment, and Engineering teams and requires a full-time commitment of at least five months.

Intern will develop AI-enabled analytics, automation workflows, dashboards, and software solutions for NAND semiconductor test engineering. Responsibilities include analyzing manufacturing and test datasets, automating test-result analysis and validation, correlating wafer yields, exploring machine learning for predictive insights, and improving test quality, productivity, and engineering cycle time. The role provides hands-on exposure to wafer probe, burn-in, assembly testing, and high-volume semiconductor manufacturing while collaborating with engineering, manufacturing, quality, and data science teams.