鴻佰科技(鴻海集團)

1. 負責資訊系統軟體開發專案、多系統整合專案。撰寫軟體專案規格書及維護專案相關文件2. 專案資源整合、開發時程管控、問題追蹤/解決、風險管控。3. 跨部門溝通協調。4. 完成主管交辦事項

1. 負責開發與維護串接系統平臺的移動端APP2. 與 UX/UI 設計師合作、規劃介面3. 與 PM 協作溝通，確認客戶需求，並確實掌握開發進度與品質

1. 研究雲儲存元件和新功能、新版本開發演進，及系統優化，進行功能導入設計2. 雲儲存應用服務整合設計與開發3. 協助存儲平台問題釐清解決與設計優化4. 開發自動化佈署套件5. 協助客戶資料中心運維技術支援

1. 以 AI/ML 專業完成滿足業務需求的演算法與相關功能2. 規劃數據模型，進行統計與分析，開發資料視覺化圖表3. 執行機器學習專案，設計、建置與上線

1. 電腦視覺/語音辨識/自然語言演算法應用開發2. 深度學習演算法開發3. 深度學習框架硬體加速優化

1.主技術架構評估及選擇2.系統架構設計、維護、改良3.需求分析4.系統設計5.平臺、API 功能開發與優化

1.雲端平台運維(主機維護、監控、故障排除)2.虛擬主機應用/服務管理，平台資源管理3.SOP手冊撰寫4. 伺服器設備維護、故障排除5. 第一線及第二線客戶系統問題解決與技術諮詢

1.負責與海外客戶在平台操作與應用上的溝通。2.對客戶說明解說平臺操作, 溝通協調相關平臺導入細節。3.處理客戶問題和客戶 concall定期追蹤及更新進度。4.了解客戶需求，與開發部門協調，追蹤需求開發進度以及回報客戶。5.完成英文產品使用說明書，包含培訓資料的撰寫。6.企業內外策略合作擬定，合約簽訂。 7.推廣策略功能企劃，功能測試與調適。8.平台維護運營, 數據維護和定時更新平台資訊。

1.伺服器硬體測試及功能驗證2.伺服器供裝與上架3.伺服器設備維護、故障排除4.伺服器設備庫存管理5.工作流程改善，更新工作SOP6.硬體RMA

"Job Summary:The Machine Learning engineer will be responsible for computer vision related projects, particularly in advanced image/video processing analyses and utilized for improving product quality, production yield, and factory effectiveness, along with other RD activities such as algorithm designs, prototype developments and experimental designs. Key Responsibilities:• Design, implement, and refine advanced Machine Learning/Deep Learning models to support product quality improvement, increasing yield and factory effectiveness.• Cultivate strong relationships with production line engineers, IT, and other key stakeholders to ensure alignment of modeling initiatives with company objectives and to identify new hypotheses for model improvements.• Scale out modeling capacity by driving infrastructure improvements such as automation of data preparations, model training, implementation, and optimization.• Apply deep learning and computer vision techniques, such as image classification, object detection, and support integration of models into tools for use by product engineers and business analysts.• Engage with customers to develop and customized data analytics solutions to address special needs.• Address ad hoc queries from management and present actionable recommendations in a clear, concise, and convincing manner.• Communicate the application and benefits of using various modeling techniques to improve decision-making to customers and stakeholders.• Collaborate effectively with team members, whether leading projects or supporting initiatives led by others. • Research and evaluate new data technology and state-of-art algorithms, and keep up to date with market trends and competitive insights."