Top AI Jobs in Singapore

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 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.

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.

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.

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.

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.

Manage network tool utilization strategies, benchmark performance, and optimize manufacturing capacity, equipment deployment, and capital investments. Develop and communicate improvement plans across manufacturing teams, assess capacity impacts from process changes, and collaborate on tool and process roadmaps. Apply AI to improve investment decisions, process flexibility, capacity sharing, and equipment repurposing. Identify discrepancies and drive resolutions in a changing environment.

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.

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.

Bridges business, product, operations, and technology teams by eliciting requirements, translating them into technical solutions, analyzing data, creating insights, and supporting architecture, governance, and documentation. Uses authorized AI capabilities responsibly to accelerate analysis and validates outputs for accuracy and data sensitivity. Develops dashboards, reporting, and data-driven recommendations for strategic decision-making.

Design, deploy, and optimize agentic AI workflows and integrations for enterprise customers. Lead implementations from scoping through adoption, connect agents to customer data and systems, establish prompts, evaluations, guardrails, and human oversight, and coordinate engineering, data science, product, and customer success teams. Serve as the primary technical customer partner while managing roadmaps, requirements, delivery risks, and measurable implementation outcomes.

Owns the identification, prioritization, and implementation of AI solutions that reduce costs across procurement, manufacturing, planning, and program management. Collaborates with data scientists, data engineers, and global business teams to develop business cases, validate ROI, monitor financial and operational impact, and establish new AI use cases. Requires strong cost-project experience, analytical ability, communication skills, and cross-functional leadership, preferably in the semiconductor industry.

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.

Support the Product Owner in delivering an enterprise LLM productivity tool. Responsibilities include roadmap execution, product vision, feature planning, user research, MI analysis, requirements gathering, backlog prioritization, engineering collaboration, and adoption support. The role requires familiarity with generative AI, prompt engineering, model evaluation, AI safety, and large-scale data, analytics, or AI transformation initiatives in financial services or consulting.

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.

Five-month internship focused on SSD depanel process characterization and optimization in semiconductor manufacturing. Responsibilities include executing statistical Design of Experiments, analyzing process and equipment data, identifying variation sources, establishing operating windows, developing visualizations, collaborating with engineering stakeholders, and evaluating AI-enabled tools for automated analysis, anomaly detection, reporting, and knowledge capture.

Manages end-to-end procurement for capital equipment, spares, and services, including P2P processes, supplier relationships, negotiations, contracts, delivery, cost optimization, and performance management. Drives localization, supply-chain resilience, continuous improvement, and AI-enabled procurement initiatives. Partners with Procurement, Engineering, Planning, Finance, and Legal teams while providing strategic recommendations and executive-level supplier insights.

Intern will map High Bandwidth Memory sample workflows, clean and analyze manufacturing data, develop predictive models, forecast burn-in resource demand, and build Power BI or Tableau dashboards and automated alerts. The role supports workflow optimization, risk monitoring, process documentation, and stakeholder recommendations across semiconductor planning and reliability operations. Candidates gain experience in predictive analytics, business intelligence, AI-enabled workflows, and manufacturing systems.

Interns will develop AI-enabled and digital solutions for semiconductor failure analysis workflows. Responsibilities include analyzing laboratory metrics and engineering datasets, creating dashboards and automation tools, exploring AI and knowledge-management applications, collaborating with Test Engineering stakeholders, and presenting project findings. The role provides exposure to electrical and physical failure analysis, semiconductor manufacturing, data analytics, workflow automation, and engineering decision-making.

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.

Five-month internship focused on applying data analytics and machine learning to semiconductor manufacturing data. The intern will query and preprocess large-scale quality datasets, develop models for quality-metric drift detection, perform multivariable analysis and optimization, create visualizations, and automate engineering workflows. Responsibilities include collaborating with engineering teams, documenting results, and presenting recommendations. Relevant backgrounds include engineering, statistics, mathematics, computer science, data science, or another analytics-related discipline.

Lead global teams for HBM customer integration and system engineering, drive technical interlocks, design reviews, escalations, and integration. Partner with design, product, manufacturing to translate customer requirements into product solutions. Own HBM architecture, packaging, manufacturing, customer enablement, scalable engagement models, governance, and executive communications. Resolve complex technical issues and influence product roadmaps. Develop and deploy AI systems to automate processes and solve technical challenges.