找工作

computer vision, NLP, and other technologies into existing products and future applications. 2.產品領域為智慧製造

Overview of Role: As a ML/AI Engineer in Corporate Planning Organization, you will have the unique opportunity

1. Actively pursue new business opportunities. 2. Identify market trends, evaluate market potential, and formulate strategies in the cell therapy and pharmaceutical industries. 3. Deliver presentations and implement development projects. 4. Cross-functional communication with the R&D and financing teams may be an additional responsibility.

熟悉自然語言處理 (NPL)，讓機器人可進行語音辨識、情感識別 2. 熟悉機器學習、強化學習等AI訓練，給予機器人決策、行為生成能力

我們想要找熱愛 AI 持續不斷學習新技術或打比賽, 聚焦長遠目標, 並且真正動手解決問題的人. 歡迎加入我們.

【具備條件】 1、計算機、數學、物理及工程相關專業大學及以上學歴； 2、至少熟練掌握C++、Python和腳本語言中的一種； 3、熟悉Linux環境，熟悉Tensorflow、PyTorch等主流深度學習框架中的一種

【具備條件】 1、計算機、數學、物理及工程相關專業大學及以上學歴； 2、至少熟練掌握C++、Python和腳本語言中的一種； 3、熟悉Linux環境，熟悉Tensorflow、PyTorch等主流深度學習框架中的一種

passionate about extending AI/ML expertise.

•我們在一個節奏快且敏捷的工作環境, 聚焦長期目標, 動手解決真正問題, 將 AI 落地在真實世界, 並發表論文在頂級會議與期刊. 歡迎加入我們.

【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=306&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. Responsibilities: 1. GPU computation for mask defect detection. 2. Transformer/style transfer to simulate tool’s inspection images for inline defect check. 3. CNN for auto defect classification.