Top AI Jobs in Singapore

Leads the AI vision, strategy, and execution agenda across Mastercard’s Marketing Services portfolio. Identifies and scales AI-powered products, capabilities, platforms, workflows, and growth opportunities. Partners with Product, Engineering, Data Science, and enterprise technology teams to embed predictive analytics, generative AI, and agentic capabilities into customer-facing and internal solutions. Drives cross-functional prioritization, operational scalability, strategic partnerships, and responsible AI adoption while strengthening marketing innovation and business performance.

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.

Develop and optimize photolithography processes for advanced 3D NAND manufacturing, improving yield, quality, process margins, and cost. Apply artificial intelligence to create photolithography process-development algorithms, evaluate hardware and novel processes, and implement process monitoring and control methods. Collaborate with manufacturing, R&D, suppliers, and global teams to troubleshoot integration issues, adapt technology for future nodes, identify simplification opportunities, and drive technical breakthroughs through patents and publications.

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.

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.

Develop an AI-enabled application, analytical model, or automated workflow addressing a semiconductor process or equipment engineering challenge. Analyze manufacturing and engineering data using statistics, machine learning, Generative AI, large language models, visualization, or automation. Test, validate, document, and present the solution, demonstrating potential improvements in yield, quality, cost, productivity, or cycle time.

Own smart manufacturing product solutions from problem definition through deployment, adoption, and value realization. Gather business requirements, define solution scope and KPIs, prioritize improvement opportunities, and lead cross-functional projects with data scientists, data engineers, suppliers, and manufacturing stakeholders. Use operational data, AI, machine learning, and automation to improve wafer output, productivity, decision-making, and capital efficiency.

Leads High Bandwidth Memory product development from introduction through high-volume production. Owns technical program requirements, milestones, reviews, risk mitigation, decision-making, and cross-functional coordination across engineering, quality, supply chain, packaging, test, and manufacturing teams. Represents programs to executives, drives change management, and develops distributed team members through mentorship, coaching, evaluations, and accountability.

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.

Develop software and data-driven solutions for semiconductor probe operations. Responsibilities include building real-time Tableau reporting and monitoring, automating material tracking and product validation, improving issue-resolution turnaround times, identifying process improvements through analytics, and collaborating with global Probe teams. The role also involves responsibly integrating AI-assisted tools and supporting continuous improvement across Engineering and Production operations.

Analyze semiconductor packaging, assembly, test, inline signals, process parameters, and manufacturing data to identify process variability and yield-loss contributors. Apply statistical analysis, visualization, programming, and AI-enabled workflows to investigate reject rates, develop engineering recommendations, document findings, and present results through a technical report and presentation.

Lead data science strategy for AML and financial crime risk controls. Develop AI-powered screening, entity resolution, graph and network intelligence, anomaly detection, transaction monitoring, and proactive discovery of emerging threats. Partner with Product, Engineering, Compliance, and Operations to deliver scalable production controls, influence the roadmap, establish reusable frameworks, and mentor data scientists.

Supports institutional clients investing in private-market infrastructure across Japan and APAC. Responsibilities include client servicing, investor reporting, content production, Japanese-language presentations and translations, regulatory reporting, fundraising support, issue resolution, and process improvement. The role partners with investment, product, operations, technology, and data teams to improve reporting efficiency through AI and automation while delivering tailored client experiences.

Manage semiconductor test capacity modeling, network balancing, tooling transfers, capacity constraint mitigation, tester investment planning, and quarterly scenario reviews across manufacturing sites. Coordinate with procurement, planning, engineering, and site teams to optimize tooling deployment and supply capacity. Lead digital transformation initiatives, capacity simulations, workflow automation, and AI-agent development for planning, risk analysis, and tooling management.

Supports an AI-enabled procurement transformation project focused on procurement and supply-chain analytics, inventory risk analysis, workflow improvement, dashboards, and automation. The intern will analyze procurement data, develop tracking and analytics solutions, prototype Agentic AI or automation tools, collaborate with global stakeholders, document process improvements, and present project outcomes and recommendations.

Develop an AI-enabled automation solution for low-yield analysis in semiconductor memory testing. The intern will study test operations, manufacturing systems, test methodologies, data flows, and lot-disposition processes; apply programming, analytics, visualization, and AI tools; validate improvements in efficiency, accuracy, and consistency; and document findings through a final report and presentation.

Lead global procurement and category strategies for semiconductor capital equipment. Responsibilities include complex commercial negotiations, supplier segmentation and governance, supply assurance, capacity planning, cost optimization, supplier performance improvement, and executive relationship management. The role also applies AI-powered tools, predictive analytics, automation, and business intelligence to improve sourcing efficiency, identify risks, and support strategic decisions across Micron’s technology development and manufacturing roadmap.

Develop a centralized Power BI Enterprise Metrics Hub integrating data from multiple reporting platforms. Responsibilities include defining KPIs, designing an enterprise data model, building interactive dashboards, automating refreshes, analyzing process-control and operational metrics, generating AI-enabled insights, and presenting recommendations. The intern will collaborate with engineering, manufacturing, quality, and analytics stakeholders while producing documentation and knowledge-transfer materials.

Analyze semiconductor manufacturing signals, process parameters, and test results using Python, SQL, statistics, visualization, and AI-enabled methods. Identify sources of variability, yield loss, and product rejects; develop analytical models and data-driven recommendations for process stability and quality improvement. Document findings, prepare technical reports and presentations, and collaborate with cross-functional engineering stakeholders during a five-month full-time internship.

Participate in a five-month project optimizing NAND component test flows through manufacturing data analytics, automation, statistical analysis, machine learning, and enterprise AI. Retrieve, prepare, analyze, and visualize manufacturing data; develop scripts, models, reports, and automation tools; identify product recovery and test-flow improvement opportunities; validate AI-generated outputs; and present documented findings and recommendations. Collaborate with engineers while strengthening technical documentation, communication, and problem-solving skills.

Develop a prototype AI-enabled equipment health monitoring and reliability analytics framework. Analyze alarms, downtime, maintenance, and performance data; create health indicators; apply statistical and machine learning methods for anomaly detection and degradation analysis; build an intelligent monitoring agent and interactive dashboard; and document and present findings to engineering stakeholders.

Lead development and execution of global alignment and standardization programs (TPM/BKM) across fab process areas. Drive tool utilization, ESTA transfers, SEAL system deployment, audits, and closure of area alignment projects. Coach and certify TPM core teams, partner with IT/CPEE, define metrics, and report progress to site leadership to improve speed, quality, cost, and people outcomes.

Manage the full sales cycle for mid-enterprise and enterprise prospects across Greater China, including qualification, demonstrations, pipeline development, forecasting, strategic deal execution, and closing. Build relationships with clients, agencies, and internal stakeholders while collaborating across product, engineering, partnerships, marketing, operations, enablement, and customer success. Provide guidance to newer account executives and use AI to improve sales workflows.

Win and grow Braze AI business by engaging senior customer stakeholders, leading AI solution discussions, quantifying business impact, supporting proofs of value, enabling sales colleagues on reinforcement learning, and communicating customer needs to product and marketing teams. Represent Braze AI at meetings, events, conferences, and trade shows while coordinating pre-sales, post-sales, and technical implementation teams.

Leads smart manufacturing data science initiatives for the F10 organization, serving as the bridge between site leadership, users, and enterprise teams. Responsibilities include prioritizing requirements, driving solution adoption, balancing local support with network best-practice deployment, evaluating capabilities, coordinating cross-functional projects, monitoring deliverables, and managing competing resources and priorities.