面議（經常性薪資達4萬元或以上） 新竹市 3年工作經驗 22天前更新
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 Engineer in the Product Innovation department, you will collaborate closely with product managers, designers, and internal business users to prototype and integrate new features into products. You are self-motivated and naturally curious, driven to innovate and deliver impactful results.
Responsibilities:
1. Drive Innovation and Impact: Pioneer novel AI/ML solutions from initial concept to functional prototype. Shape the future of our internal product with your discoveries.
2. Collaborate with Business Users: Work closely with internal stakeholders to understand needs and translate them into actionable AI-driven solutions that create measurable value.
3. Apply Smart AI Techniques: Choose and implement the appropriate methods—classic machine learning, deep learning, or generative AI—to effectively solve diverse problems.
4. Partner Across Teams and Geographies: Collaborate with cross-functional, global teams including AI researchers, engineers, and domain experts to integrate AI into production systems.
5. Share Knowledge and Stay Current: Communicate insights through data storytelling, mentor colleagues, and proactively adopt emerging AI/ML trends to continuously improve solutions.
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