Top Product Management Jobs in Singapore

Support AI product management projects within global procurement by analyzing workflows, translating user needs into product requirements, designing and testing agentic AI solutions, evaluating adoption and effectiveness, and developing responsible-AI learning materials. The intern will work with tools such as Claude Cowork and Microsoft Copilot Studio, assess data readiness, gather user feedback, measure business impact, and present recommendations for AI-enabled procurement improvements.

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.

Lead definition, development, and delivery of Industry 4.0 smart manufacturing products. Own product roadmap, gather and prioritize requirements, coordinate engineering, data science, and operations, deploy data-driven solutions, ensure data quality, build UI visualizations, and scale standardized tools and processes across global sites.

Lead AI-enabled cost transformation across procurement and manufacturing. Own product backlog and roadmap, define requirements with data scientists and engineers, prioritize AI/Generative AI cost use cases, drive delivery, measure before/after savings, and embed workflow optimizations into daily operations.

Lead operations engagement for early lifecycle High Bandwidth Memory (HBM) NPI products: align supply chain, manufacturing, procurement, and logistics; manage BOM governance and risk reviews; secure prototype and qualified silicon/capacity; maintain ramp schedules, oversee sample delivery and OTD, remove supply-demand roadblocks, and report operations risks to stakeholders.

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.

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.

Owns end-to-end smart manufacturing and AI product initiatives, translating semiconductor manufacturing needs into requirements, user stories, success criteria, and deployment plans. Partners with data scientists, engineers, suppliers, and global stakeholders to deliver machine learning, analytics, automation, and IIoT solutions. Identifies operational improvement opportunities using manufacturing data and KPIs, leads cross-functional implementation and adoption, and drives measurable gains in wafer output, productivity, yield, quality, and capital efficiency.

Own the strategic roadmap for AI-enabled yield smart manufacturing solutions. Identify solution gaps, define business opportunities, and lead global projects with fab engineers, AI engineers, and data scientists. Apply AI, GenAI, predictive analytics, and machine learning to yield improvement, process optimization, technology development, and intelligent decision support. Use performance metrics and domain expertise to address manufacturing challenges and deliver integrated solutions.

Own smart manufacturing and AI-enabled yield analysis solutions from discovery through implementation. Diagnose process gaps, define requirements with Industry 4.0 users, standardize scalable tools, build ROI-based business cases, prioritize initiatives, and coordinate global teams including architects, data scientists, data engineers, and machine learning engineers. Use operational metrics to identify improvements and provide functional guidance on system capabilities and interfaces.