面試經驗談專區

1. 熟 JAVA, 資料庫應用, 及網頁設計語言(Thymeleaf, HTML, Javascript,CCS 等)者佳 2. 熟悉 JSP/Servlet 技術,了解 J2EE 概念 3. 懂 Spring framework, JPA, HIBERNATE 等 open-source 技術架構 4. 熟 Java Web AP 開發架構者 (含: Spring, Spring boot, Struts, Hibernate… 等) 5. 有Git 使用經驗 6.有 docker或k8s佈署經驗尤佳

1. 規劃伺服器及Rack Level產品自動化測試方案 2. 規劃及開發 Rack Level 自動化測試程式 3. 規劃及導入實驗室或工廠自動化測試 4. 規劃及開發客戶或實驗室需求的軟體工具 5. 協助研發單位規劃自動化測試需求

1.數據監控Web程式開發與設計 2.雲端應用服務功能開發 3.使用者介面程式開發 4.軟體模組開發與整合

1. 根據客戶應用需求,提供雲端產品技術整合之系統架構,提供符合客戶需求之產品服務 2. 跨部門協調研發及生產單位,提供系統整合產品服務 3. 研究及分析雲服務市場需求並設計符合客戶需求之產品

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 R&D 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.

• Major tasks focusing on data center devices, including AI accelerators, servers, storage, Ethernet switches, and power shelf. • Development of hardware diagnostics software • Development of automated testing processes for products • Integration or development of software for product stress testing • Support for manufacturing test development during new product introduction

＊了解虛擬化VDI 應用 ＊Restful API呼叫、設計以及程式撰寫。 ＊進行開發前後功能之相容測試與除錯修改、規格技術文件撰寫。 ＊協助研發網站新技術與新工具。 ＊提升自我網站前後端技術，行動應用及網路發展趨勢

1. 研究雲平台核心元件和新功能、新版本開發演進，及系統優化，進行功能導入設計 2. 平台上層應用服務整合設計與開發 3. 協助平台問題釐清解決與設計優化 4. 平台架構設計與優化

• 規劃AI服務架構，協助客戶導入。 • AI相關數據架構、建模、應用分析規劃。 • AI相關產品、技術學習研究。

1. Develop Cluster Deployment/Management/Monitor Modules 2. Big Data Platform Operation (Hadoop, Spark, HBase, ...) 3. Support Customer to Maintain Big Data Platform

1. 負責AI應用資料視覺化顯示與雲端顯示介面 2. 協助AI Framework雲端顯示介面開發 3. 持續學習新技術並導入相關系統開發

1. Web 程式設計與開發。 2. Web 介面設計與開發。 3. 開發與整合Kubernetes相關服務。

＊對於開發Java 網站有開發經驗 ＊了解Alfresco 架構與相似經驗開發。 ＊進行開發前後功能之相容測試與除錯修改、規格技術文件撰寫。 ＊協助研發網站新技術與新工具。 ＊提升自我網站前後端技術，行動應用及網路發展趨勢

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.董事會及功能性委員事項 2.股東會年報/議事冊編制 3.關聯公司董事會/股務事務 4.重大訊息公告 5.董事會績效評鑑事宜 6.ESG例會G小組考核指標回覆

你會進入電動車的核心作業系統團隊，負責車內軟體的整體架構開發，提供車內軟體服務與控制系統整合執行框架，降低軟體開發的複雜度。你的工作內容包含： 1. 設計並開發車內軟體系統架構，確保能符合功能需求規範 2.建立模組化開發流程，促進各模組獨立開發 3.導入軟體工具，加速開發時程並降低複雜度 4.建立編譯與 CI/CD 系統，將各模組自動化整合編譯成為最終軟體映像 5.使用並熟悉整車軟體設計開發工具

Project Managers who are responsible for the overall direction, coordination, implementation, execution, control and completion of specific projects ensuring consistency with company strategy, commitments and goals. 1. Familiar with project management tools, strategic planning and risk management techniques. 2. Demonstrated ability to motivate / drive multidisciplinary teams to achieve objectives (performance, quality, cost, timelines) 3. Lead and coordinate the project teams to achieve the project scope, goals and deliverables 4. Monitor project KPIs and ensure adherence to commitments. Report to senior management on regular base. 5. Interact with customers: facilitate a bi-directional communication. (requirements, status, decision to be made, etc...) 6. Manage project budgets and BoM cost 7. Plan and schedule project timelines 8. Constantly monitor and report on progress of the project to all stakeholders 9. Present reports defining project progress, problems and solutions 10. Implement and manage project changes and interventions to achieve project outputs

你會進入電動車的核心作業系統團隊，負責開發各項車內軟體服務，透過網路讓車內主機相互溝通，傳遞控制命令與狀態訊號，並確保實時性與穩定性。你的工作內容包含： 1. 開發與維護車內軟體服務，進行功能開發 2. 參與軟體系統架構設計，定義車內通訊服務介面 3. 與底層軟體團隊合作，確保整體系統符合功能需求規範 4. 建立軟體設計規格文件 5. 使用並熟悉各項車用軟體開發工具

1.AIOT系統管理開發,應用於智慧工廠(智能安防與流程監控) 2.負責管理平台之 UI/UX 設計開發 3.串接後端 API，實現數據即時同步與高互動的使用介面 4.開發儀表板，將數據與分析結果以圖表直觀呈現，輔助決策 5.優化大量數據呈現時的瀏覽器效能，設計多維度的數據篩選與查詢機制

＜About the job＞ As the AI Software Engineer, you‘ll join the various advanced Data Science & AI Projects in the corporate headquarters. As well as developing intelligent applications via related AI and Big Data Analytics Technology for digital transformation, you will have plenty of opportunities to develop emerging applications based on different use cases and expand your tech skillset in this world-class company (Fortune Global 500, 20th). ＜Job Description＞ Responsible for deploying the AI/Data Science collaborative framework and building the AI model and data operating infrastructure. Using software development experience to design and develop high-performance automated systems for AI development and operation. As below: ．Collaborating with Data Scientist/AI ML Engineer team, other software system development teams, and the infrastructure team. ．Ability to utilize various tools/methods to build the MLOps/DataOps/DevOps and deploy and manage the AI Development framework and infrastructure ．Developing infrastructures for data transformation and ingestion and automating important infrastructure to process data ．Deploy AI models to the Inference server and optimize the performance of the model serving operation reliably and efficiently. ．Assist the Data Scientist/AI ML Engineer team in converting the AI models into APIs to serve other systems or integrate with other systems. ＜Skill Sets＞ (1)Excellent problem-solving and troubleshooting skills. (2)Genuine passion for learning new technologies and open-source projects. (3)Familiarity with Python and Java (python is a must) (4)Good understanding of the Linux OS environment, the Shell Scripting, and infrastructure/networking knowledge. (5)Experience with GitLab CI/CD (Nice to have but not necessary) (1)Experience with MLops and Model Serving tools. (2)Experience in GPU programming and performance tuning (3)Being familiar with AZURE (or AWS) cloud infrastructure will be a plus (4)Familiar with declarative infrastructure/container technologies, such as Docker and Kubernetes (k8s/k3s)