Top AI Jobs in Singapore

Owns pre-silicon validation, simulation regression, post-silicon characterization, and simulation-to-silicon correlation for NAND test chip vehicles. Analyzes device and architecture sensitivities, defines test methodologies, leads root-cause investigations, and drives silicon learning across design, process, technology, and test teams. The role also develops reusable technical methods, influences cross-functional decisions, mentors engineers, and applies data analytics, machine learning, and AI-assisted tools.

Leads strategic programs enabling scalable engineering execution aligned with product roadmaps. Owns PSE’s AI strategy, drives AI-enabled tools and future-of-work initiatives, establishes KPIs, improves organizational structures and processes, and provides executive-ready insights. Partners with global engineering leaders to close capability gaps, strengthen cross-functional execution, and improve organizational effectiveness across complex, matrixed environments.

Manage supplier supply assurance, purchase orders, forecasts, capacity planning, lead times, safety stock, supply allocation, and shortage resolution across a global manufacturing network. Lead supplier reviews, negotiate capacity and lead times, monitor delivery metrics, manage product and process end-of-life planning, update supply systems, and drive process improvements using AI and operational best practices.

Analyzes logistics performance, transportation costs, inventory flows, service levels, and operational KPIs. Leads global logistics transformation projects, develops dashboards and reports, identifies cost-saving opportunities, and implements AI, automation, and digital workflow solutions. Manages logistics systems including SAP and transportation platforms, gathers requirements, coordinates testing and deployments, maintains documentation, supports training, and drives process standardization, governance, continuous improvement, and logistics network optimization.

Lead cybersecurity operations focused on threat detection, incident response, vulnerability analysis, security infrastructure, and security strategy. Develop policies, monitor complex systems, investigate threats, validate AI-assisted findings, and collaborate across teams to improve security, resiliency, auditability, and operational excellence across on-premises, cloud, and hybrid environments.

Intern will develop an AI-enabled inline health-monitoring and process-drift detection solution for semiconductor Process Integration. Responsibilities include extracting and validating process metrics, creating dashboards and visualizations, analyzing large datasets, exploring AI tools for process-window optimization, and prototyping AI agents for engineering workflow automation. The intern will collaborate with engineers, document findings, and deliver a reusable monitoring solution and handover package.

Monitor and optimize inbound and outbound transportation, freight costs, carrier performance, shipment fulfillment, customs compliance, and logistics KPIs. Analyze supply chain data, identify bottlenecks and cost-saving opportunities, support carrier negotiations, maintain ERP and reporting systems, develop dashboards, and assist with risk mitigation, process automation, and network optimization.

Conduct a five-month engineering project optimizing Chemical Mechanical Planarization processes and characterizing equipment in semiconductor manufacturing. Analyze process, metrology, equipment, and manufacturing data using statistical and AI-assisted methods; assess process capability and qualification results; and develop a dashboard, analytics model, or automation tool. Collaborate with cross-functional stakeholders and deliver technical reports, presentations, engineering recommendations, and documented improvement results focused on stability, yield, cost, productivity, or data accessibility.

Five-month internship developing AI and machine learning solutions for semiconductor facilities engineering. Responsibilities include analyzing operational and sensor data, building predictive maintenance and anomaly-detection prototypes, creating dashboards and automation workflows, and developing AI-enabled knowledge-management tools. The intern will collaborate with facilities engineers, apply software-engineering principles, document findings, and present recommendations and business value.

Conduct experiments to improve poly-SiGe gap filling in high-aspect-ratio semiconductor structures. Analyze deposition effects on film growth, conformality, voids, seams, pinch-off, and structural integrity using DOE, SEM/TEM cross-sections, and statistical methods. Correlate fill quality with die strength and wafer or block bending, then recommend optimized process windows and qualification plans. Collaborate with engineering teams and subject matter experts throughout the development cycle.

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 semiconductor HBM reliability, device/package/wafer testing, failure analysis, product debugging, laboratory operations, inventory and logistics, audits, safety compliance, automation, data analysis, and continuous improvement. Uses AI-assisted tools, Power BI, Python, SQL, and manufacturing systems to improve reliability workflows and debug efficiency. Requires rotating day/night shifts, including occasional weekends and public holidays, and collaborates with cross-functional teams while mentoring junior technicians.

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.

Develop an AI-powered sustainability command center using energy, water, utility, cost, and carbon data. Responsibilities include assessing data sources, building structured data models and processing workflows, creating Power BI dashboards, applying analytics and AI for anomaly detection and insight generation, automating reporting, tracking sustainability opportunities, and preparing technical documentation and user 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.

Full-time internship focused on applying Python, statistical analysis, visualization, and introductory machine learning to semiconductor probe-test, electrical failure, and fabrication-process data. The intern will investigate yield behavior in advanced memory manufacturing, develop a multivariate analytics tool, identify potential yield-improvement opportunities, and present documented findings through a technical report and presentation.

Develop an AI-enabled proof of concept for New Product Manufacturing, using Generative AI, analytics, dashboards, automation, Python, SQL, and Microsoft tools. The intern will assess manufacturing processes, define data and business requirements, automate reporting or workflows, create operational visualizations, measure productivity benefits, and document recommendations. The role involves collaboration with engineering, manufacturing, data, automation, and business stakeholders.

Intern will analyze Wafer Intelligent Scanner, defect, yield, process, and equipment data to identify abnormal wafer bevel behavior and early indicators of defects. Responsibilities include data preparation, statistical and machine learning analysis, model evaluation, dashboard creation, and technical reporting. The project supports semiconductor yield improvement and defect reduction through AI-enabled manufacturing analytics.

Lead global contamination-control strategy across semiconductor wafer fabs, improving yield, reliability, throughput, and cost. Responsibilities include contamination-risk mitigation, process and equipment optimization, capacity expansion support, wafer-shipment controls, KPI development, supplier collaboration, SOP standardization, and cross-functional project leadership. The role requires driving data-based monitoring, resolving process issues, supporting qualifications, coordinating global teams, and communicating outcomes across manufacturing sites.

Coordinates first-of-a-kind chemical setup across Micron’s global manufacturing network. Ensures chemical, supplier, regulatory, EHS, and data-quality information is complete and traceable across CEDAR, SAP, and related workflows. Partners with sites, suppliers, procurement, engineering, and master data teams to resolve issues, improve governance, and support SAP S/4HANA transition. Uses AI, automation, and analytics to identify compliance risks, improve workflows, and strengthen chemical-management processes while preserving site-level EHS approval authority.

Contribute to semiconductor manufacturing EHS projects involving compliance tracking, risk monitoring, environmental compliance, safety initiatives, data analysis, dashboards, automation workflows, and AI-enabled solutions. The intern will complete an improvement project, develop recommendations and an implementation plan, and present findings. The five-month internship provides practical experience with ISO 14001, ISO 45001, workplace safety, risk assessment, digitalization, and continuous improvement.

Serves as the primary HR partner for employees, managers, and regional leaders across APJ. Responsibilities include employee relations, performance management, engagement, onboarding, offboarding, employment compliance, HR reporting, talent programs, manager coaching, and organizational change. The role advises senior leaders, supports local employment practices across APJ markets, partners with global HR teams in a matrixed environment, and uses people data, automation, AI, and HR technology to improve employee experiences and decision-making.

Intern will develop software, data pipelines, integrations, dashboards, automation, and AI-enabled solutions for photolithography engineering in semiconductor manufacturing. Responsibilities include connecting equipment, manufacturing systems, databases, and engineering platforms; applying analytics and machine learning; and using modern software practices such as version control, testing, deployment, and maintainable architecture. The intern will collaborate with multidisciplinary engineering teams and deliver production-quality applications, documentation, reusable code, and a final technical presentation.

Manage strategic supplier relationships, category sourcing, RFx processes, contract negotiations, supplier performance, cost optimization, risk mitigation, and procurement compliance. Partner with cross-functional and global teams while using analytics, digital tools, and AI technologies to improve procurement efficiency and decision-making. Support budgeting, CAPEX planning, savings tracking, supplier audits, and continuous improvement initiatives.

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.