Top AI Jobs in Singapore

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.

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.

Leads global manufacturing equipment and capacity modeling, optimizing tool utilization, throughput, capital deployment, process flexibility, and equipment repurposing. Analyzes the financial and operational impacts of manufacturing changes, develops benchmarks and reports, and coordinates implementation across manufacturing, engineering, finance, procurement, supply chain, production, and planning teams. The role also explores AI-enabled tools to improve planning, reporting, and optimization.

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.

Supports global HR services transformation initiatives focused on AI, automation, productivity, and digital service delivery. Coordinates project execution, requirements, testing, rollout, stakeholder adoption, process optimization, documentation, reporting, and continuous improvement. Partners with HR teams, technology groups, and vendors while tracking productivity, experience, and adoption outcomes.

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.

Owns development, qualification, and deployment of advanced semiconductor metrology applications for 3D NAND process development. The role focuses on FIB and complementary techniques such as AFM, SEM, and WLI, while evaluating next-generation systems, developing technology roadmaps, partnering with suppliers, and applying AI, machine learning, and data analytics to improve defect detection, yield, reliability, and manufacturing readiness.

Leads Micron’s global Photo MAP organization, overseeing photolithography, metrology, application, and process performance across semiconductor manufacturing sites. Develops technology roadmaps, improves productivity and overlay control, drives AI-enabled digital transformation, supports factory expansions, and standardizes best practices. Partners with manufacturing, technology development, process integration, and suppliers while building global teams, developing talent, managing strategic initiatives, and aligning manufacturing capabilities with business objectives.

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.

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

Supports a five-month engineering project improving solid-state drive product development workflows. Responsibilities include analyzing engineering processes, developing Python scripts, SQL data pipelines, dashboards, automation solutions, and visualizations, and evaluating their effectiveness. The intern collaborates with engineering and cross-functional stakeholders to define requirements, validate solutions, document findings, and present recommendations. The role provides exposure to semiconductor manufacturing, engineering data analysis, workflow automation, and potentially AI-enabled information retrieval.

Intern will develop AI-enabled procurement analytics, dashboards, and automation solutions. Responsibilities include analyzing procurement workflows, inventory, supply-chain risks, and material indicators; improving processes; applying Agentic AI, visualization, and robotic process automation; and collaborating with global stakeholders. Deliverables include an analytics solution, automation prototype, workflow review, final report, and presentation.

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.

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.

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.

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.

Develops and executes semiconductor product reliability stress tests, qualification plans, and manufacturing test strategies for High Bandwidth Memory products. Investigates reliability failures using electrical and physical failure analysis, drives root-cause resolution, supports process conversions and high-volume manufacturing, and reduces defect rates. The role manages technical risks, collaborates across fab, design, technology, quality, and systems teams, promotes AI-enabled workflow improvements, and mentors team members.

Develop and deploy machine learning, statistical modeling, and predictive analytics solutions for semiconductor manufacturing and business operations. Analyze large datasets, build scalable data workflows, conduct exploratory and root-cause analysis, and partner with engineering and software teams to operationalize models. Lead analytics projects, communicate insights to technical and business stakeholders, mentor junior data scientists, and ensure responsible, secure, compliant use of AI and data.

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.

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.

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 AI Agent prototypes and Python automation solutions to improve productivity in semiconductor photo engineering workflows. Responsibilities include analyzing engineering data, identifying automation opportunities, building data-processing pipelines, creating dashboards, evaluating solution effectiveness, documenting designs, and presenting technical findings. The intern will gain experience with generative AI, large language models, data analytics, and semiconductor manufacturing engineering.

Owns AI-driven cost-reduction solutions across procurement, facilities, construction, and tool-install processes. Partners with data scientists and engineers to identify use cases, develop business cases, prioritize projects, coordinate global implementation, and measure financial and operational impact. Requires strong analytical, communication, relationship management, and cross-functional leadership skills, with experience in cost initiatives within operations or procurement, preferably in semiconductor construction and tool-install environments.

Five-month procurement operations internship focused on AI-enabled analytics and process transformation. The intern will analyze procurement, inventory, and supply-chain data; develop dashboards, tracking tools, AI or automation prototypes; identify risks and improvement opportunities; review workflows; and present project outcomes. The role provides exposure to procurement systems, inventory analysis, supplier risk, data visualization, Agentic AI, robotic process automation, and cross-functional collaboration.

Owns AI-driven cost-reduction products and use cases across procurement, operations, engineering, and commercial functions. Collaborates with data scientists, data engineers, and global teams to implement solutions, quantify financial and operational impact, develop ROI-based business cases, prioritize projects, and identify additional opportunities. Requires strong cost-project experience, analytical skills, cross-functional leadership, communication, and relationship management.