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置為主)，並與演算法或Data團隊合作開發相關產品和應用 - 資料集分析、資料前處理、模型測試及驗證 - ML Ops模型訓練、佈署自動化 ◎《Our requirements for this role》◎ - CS/EE相關科系，有相關工作經驗者尤佳 - 精通 Python 程式

工作職責： 開發新聞內容推薦系統核心演算法 基於用戶行為和喜好建構個性化推薦 負責內容推薦、文本挖掘、用戶模型建設等 研究業界最先進的推薦算法

【我們希望您有的特質】 ★ 樂於團隊合作與知識分享 ★ 從客戶觀點出發的同理心 ★ 對技術保持熱情和好奇心 【您的任務】 ★ 參與各大AI專案，解決集團流程痛點，翻轉集團作業效率 ★ 使用統計或

工作職責： 負責優化廣告轉化的演算法開發 基於用戶行為和轉化數據，建立並優化投放策略 負責提高在線廣告的相關度、用戶體驗、投放效果及變現能力 應用機器學習等技術，使用巨量數據訓練

“Make every logistics journey your best one yet” - Quincus The Company. Founded in 2014, Quincus is a B2B supply chain operating SaaS platform headquartered in Singapore. We solve today's global supply chain challenges with groundbreaking technology. Using AI and machine learning, we have digitized and optimized the logistics process while giving customers full transparency into their supply chain. Quincus was founded by two visionary entrepreneurs who possess more than a decade of experience in

1. Improve model accuracy/performance to achieve real-time inference on edge device. 2. Iterate model to cover all kinds of common features on highway/city scene. 3. Develop a single model to simultaneously output object detection and segmentation result. 4. Apply model distillation, pruning, factorization, and quantization. 5. Data cleaning and augmentation. 6. Port to edge device, profile and find bottlenecks. 7. SOTA paper

【公司簡介】 LSC Ecosystem (鄰近桃園機場捷運A7站) 的使命是在電動載具價值鏈上扮演關鍵領航者，你想對產業發揮自己的影響力嗎？在這裡你能夠有機會在電動載具的產業裡，串連軟體與硬體、協助傳統

【關於PropTech數位人才招募計劃】 信義企業集團的各項產品與計畫正融入大數據、機器學習與人工智慧等應用，我們的數位團隊具有豐沛的研發能量，截至2023.8為止，已累積有40多件發明專利與20

【What to expect】 Here at iKala, we are developing new algorithm and data pipeline which powers business decision in marketing and in-house analytic platform. You will cowork with teams of working in Machine Learning, Data Acquisition, Data Scientist and Data Analysis to develop or optimize algorithm on large scale multi-modal data. 【What you will be doing】 1. Develop in house multilingual NLP models ( Chinese, English, Japanese ) 2. Tuning and optimize algorithm to handle

1.資料前處理: 數據清洗、特徵工程、特徵選取 2.應用數據挖掘、機器學習、深度學習、最佳化等技術，建立推薦與決策模型 3.成效指標設計，模型驗證與優化 4.模型生命週期管理，保持預測效