面議（經常性薪資達4萬元或以上） 新竹縣寶山鄉 5年工作經驗 57天前更新
【本職缺僅接受台積電官方網站投遞】
請至台積電官方網站投遞個人履歷表，此職缺履歷登錄網址: https://careers.tsmc.com/careers/JobDetail?jobId=16331&source=1111
Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. In 2023, the company served 528 customers with 11,895 products for high performance computing, smartphones, IoT, automotive, and consumer electronics, and is the world’s largest provider of logic ICs with annual capacity of 16 million 12-inch equivalent wafers. TSMC operates fabs in Taiwan as well as manufacturing subsidiaries in Washington State, Japan and China, and its ESMC subsidiary plans to begin construction on a fab in Germany in 2024. In Arizona, TSMC is building three fabs, with the first starting 4nm production in 2025, the second by 2028, and the third by the end of the decade.
The AI4BI team serves as the central intelligence hub within the Corporate Planning Organization (CPO). Our mission is to empower business users with AI-driven solutions that enhance customer satisfaction and streamline operational efficiency. We work closely with stakeholders who blend deep domain expertise in areas like demand and capacity planning with strong analytical capabilities.
As an AI Product Manager, you will collaborate with business experts to define and shape the vision and roadmap for AI products. You will partner closely with AI researchers and engineers to guide product development from concept to launch, delivering solutions that address diverse challenges while driving innovation and operational excellence.
Responsibilities:
1. Product Strategy & Vision: Establish and communicate the product vision, strategy, and roadmaps for AI/ML initiatives to advance digital transformation in CPO business processes, such as capacity planning, business forecasting, and operational optimization.
2. Cross-Functional Collaboration: Partner with cross geographical teams and functional teams, including business experts, data scientists, engineers, and external teams, to guide product development from concept to launch, and seamlessly integrate AI products into workflows and systems.
3. User Understanding: Engage closely with internal business users to understand workflows, challenges, and unmet needs. Define use cases and translate user problems into structured product requirements to ensure the successful implementation of AI solutions.
4. Problem-Solving Leadership: Frame complex problems, prioritize features, and manage competing demands to deliver innovative solutions.
5. AI to Business Impact: Convert AI/ML technical strengths into measurable business benefits, drawing on a deep understanding of product development processes.
展開 
