前端開發工程師

Ethernet Switch Development : 

1. Linux related device drivers 

2. Linux Kernel/driver/BSP Porting and Integration 

3. BMC/IPMI related firmware

＜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)

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

1. 規劃伺服器產品自動化測試方案 

2. 開發伺服器產品自動化測試程式 

3. 負責導入實驗室或工廠自動化測試 

4. 開發客戶或實驗室需求的軟體工具 

5. 協助開發研發單位自動化測試需求

1. CI/Automation/Test Automation (Python) 

2. Web Application (Python, Node.js, Java) 

3. 網管系統或 BMC/Redfish related external system (Python, Linux shell) 

4. AI, BigData, Datastore development (Python, Java)

1. 雲服務之網路架構規劃、設計 

2. SDN、NFV之規劃、導入 

3. 識別及解決網路問題 

4. 網路設備管理、維護 

5. 客戶應用上雲之網路架構諮詢、規劃

＜About the job＞： 

The Data Science & AI team of headquarter IT is developing the frontier and practical analytic technologies that enhance the data value. As the data scientist, you‘ll join the AI/Big Data Analytics program/projects related to management topics, including Commercial/Industrial Engineering/Supply Chain/Financial Performance/Operation...etc., to build the model or algorithm to empower data-driven & analytics-driven for driving business value from data insights in this world-class company (Fortune Global 500, 22nd). 

＜Job Description＞：  

．Design, implement and refine advanced Statistical Modeling/Machine Learning/Deep Learning/Numerical Simulation/Optimization Algorithm Models(at least one of the fields) 

．Ensure alignment of modeling initiatives with the requirement goal defined by key stakeholders and company objectives and identify new hypotheses for model improvements.  

．Executing big data analysis and predictive analytics projects include feature engineering, model building, algorithm development, etc.  

．Works closely with a team of data system analysts, business data analysts, data engineers, data platform architects, etc.  

．Collaborate effectively with team members, whether leading tasks or supporting initiatives led by others. 

．Self-motivated, Result-oriented, and interested in applying quantitative methods to solving business and engineering problems. 

＜Skills＞ 

．Experience with any one of Machine Learning, Statistical Modeling, Deep Learning(Nature Language/Image), Econometric Modeling, Optimization Algorithm(OR), Numerical Simulation..., etc., model/algorithm building of the practical application in the industry. 

．Familiarity with programming languages like Python or R, or Java. (Good programming skills in Python is a plus).  

．Advanced ability to perform Exploratory Data Analysis and working knowledge of statistics.  

．Ability to visualize data in the most effective way possible for a given task, especially visualize models and results and debug and troubleshoot code and models. 

．Big on finding the many insights based on the data and being passionate and patient about working with complex data.

1.遊戲軟體程式設計 

2.網路伺服器程式設計 

3.伺服器維護 

4.伺服器管理後台程式設計 

5.具好奇心, 工作熱忱、樂於學習與成長、喜歡參與開發及討論

1、使用 Unity製作遊戲相關系統功能。 

2、與專案組美術及企劃人員深入溝通，準確實現開發需求。 

3、公司現有產品維護。 

4、設計並撰寫具有彈性及可維護性佳的C#程式碼。 

5、具備Client&Server連線開發經驗，熟悉HTTP等連線方式。

協助開發跨平台應用程式 (APP/Web) 與後端 API 服務；參與軟體專案的需求訪談、功能開發與規格文件彙整。配合執行 CI/CD 自動化整合測試與程式碼審閱，支援應用 AI 模型進行任務自動化之專案實踐，並學習撰寫高品質的技術佈署文件 (TDD)。 

Assist in developing cross-platform apps and backend APIs. Participate in requirement gathering and technical specification compilation. Support CI/CD automated testing and code reviews. Collaborate on projects utilizing AI models for task automation and learn to author high-quality Technical Deployment Documents (TDD).

協助全球 AI 算力平台架構的環境佈署與配置作業；參與雲端服務資源的日常維運、自動化資源分配之參數設定及性能監控。配合利用容器化技術 (Docker/K8s) 進行效能瓶頸初步排查，支援優化 MLOps 工作流並協助撰寫技術維護文件。 

Assist in environmental deployment and configuration of global AI computing platforms. Participate in daily operations of cloud resources and parameter setting for automated resource allocation. Support initial performance troubleshooting using container technologies (Docker/K8s) and help optimize MLOps workflows and documentation.

負責產品：網路交換機/網卡 

主要職責： 

1.架設與維護自動化測試機台，確保系統穩定與可擴充性 

2.開發與維護測試腳本（Shell Script、Python），提升測試效率 

3.在 Linux 平台上進行系統安裝、配置與效能調校 

4.整合測試工具與框架，支援持續整合 (CI/CD) 流程 

5.分析測試結果，撰寫報告並提出改善建議 

6.與研發團隊合作，設計並優化測試流程 

7.支援越南工廠測試平台建置與維運（需配合出差）

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.負責後端架構設計，資料庫效能優化及系統運維 

3.建立高效可靠的串流通道，處理IOT設備大量數據存取 

4.與前端協作，產出可用於輔助決策的指標API 

5.確保系統擴展性，支援未來的數據挖掘與 AI 模型整合

To design, develop, and integrate diagnostic software solutions for servers, storage, and AI accelerator platforms, enabling automated testing and efficient issue resolution in collaboration with hardware and firmware teams. 

· Design and implement diagnostic software for hardware platforms. 

· Develop automation tools and scripts for testing and validation. 

· Integrate diagnostics with production and lab environments. 

· Troubleshoot hardware and software issues with cross-functional teams. 

· Document diagnostic procedures, tools, and technical guides. 

· Evaluate and adopt new tools or technologies to enhance diagnostics. 

Required Skills / Tools / Experience 

· Proficiency in Shell Script, Python, C/C++ 

· Strong Linux environment usage (Ubuntu preferred) 

· Knowledge of system programming, networking, algorithms, and data structures

• 規劃和執行 DevOps、CI/CD的長期策略。 

• 帶領和培養 DevOps 團隊成員，提供技術指導並進行績效評估。 

• 促進開發與營運團隊之間的協作、溝通與知識共享，強化 SRE思維。 

• 負責設計、部屬和維護自動化的 CI/CD 及品質管理 (如 Jenkins, GitLab CI, Sonarqube, 及相關監測工具等)。 

• 根據專案需求，建立、管理和維護多套應用系統環境。 

• 熟悉相關配置管理工具，確保不同環境的配置一致性。 

• 部署和管理集中式監控 (如 Prometheus, Grafana) 和日誌系統 (如 ELK Stack, Splunk)，以主動式警報和故障排除流程。

1.參與伺服器平台軟體與韌體功能之開發與維護，包含系統設計、實作與驗證。 

2.分析伺服器硬體架構與線路設計，掌握系統運作原理與軟硬體整合方式。 

3.開發與實作各式硬體介面與通訊協定（如 I²C、SPI、UART、PCIe 等），確保系統穩定運作。 

4.於 Linux 或嵌入式環境中進行開發、除錯與效能優化，熟悉版本控制與自動化流程。 

5.撰寫並維護技術文件，確保軟韌體設計具可追蹤性與可維護性。 

6.與跨部門團隊（硬體、測試、工廠製造等）協作，推進專案開發進度與功能整合。 

7.協助工廠端進行問題分析與除錯，支援產品導入與量產穩定性改善。

1. 架構設計與搭建：結合 HIS、EMR、PACS 等醫療系統需求，設計智慧醫院及機器人平台高可用資料庫架構；選型關係型 / 非關係型資料庫，搭建優化集群。 

2. 數據集成與支持：參與數據中臺建設，完成 ETL 數據整合；支持開發團隊設計評審，為科室提供技術諮詢與培訓。 

3. 安全與合規：管控數據訪問許可權，加密敏感醫療數據；配合審計與監管檢查，落實合規整改。 

4. 日常運維與監控：負責資料庫實例、許可權、性能調優；搭建監控體系（CPU、IO 等指標）；制定並執行備份恢復策略。 

5. 技術迭代與應急：評估新技術（雲資料庫、分佈式等），制定升級遷移方案；制定應急預案，處置宕機、數據損壞等突發問題。

We are seeking a highly motivated Software Team Leader, who combines technical leadership, system-level thinking, and cross-functional collaboration with R&D, Operations, and global customers to enable efficient diagnostics, automation, and intelligent data integration. 

Responsibilities 

•Lead the software team to design, develop, and integrate diagnostic software solutions for AI server and storage platforms. 

•Build a unified Diagnostics OS that supports modular and reusable test components across multiple products and customers. 

•Drive automation, standardization, and integration with production lines. 

•Collaborate with R&D and Operations to enable efficient issue diagnosis and resolution throughout the product lifecycle. 

•Develop and maintain automation tools, test scripts, and diagnostic libraries for manufacturing. 

•Define and enforce standard interfaces and log formats for seamless integration with the operation flow. 

•Document diagnostic procedures, APIs, and best practices. 

•Evaluate and adopt new tools or technologies to enhance testing efficiency and data analytics. 

Qualifications 

• Strong communication and problem-solving skills, able to respond quickly to customer and factory issues from different time zones. 

• Solid understanding of server system, AI server architecture, and diagnostics workflows. 

• Experience leading software teams and coordinating with cross-functional teams for global customers. 

• Proficient in software development lifecycle management and quality assurance practices.

1.AI / Compute / Storage伺服器測試軟體開發及相關軟體模組維護(含 板階、系統階、櫃階 測試 

2.Compute / Storage伺服器壓力測試軟體開發及維護:主要為系統階測試 

3.依伺服器組件、功能、出貨規格 建立 測試計劃，完成測試軟體套件開發後導入工廠端交付測試執行團隊: 

依專案 需短期出差美國、墨西哥 (1個月/次，年累積三個月以下)

1. 主導系統架構設計：規劃並設計次世代醫療系統（HIS）總體技術架構與演進藍圖。 

2. 微服務拆分與治理：根據醫院核心業務，主導微服務的邊界劃分、API 契約設計與服務治理策略。 

3. 數據架構規劃： 設計數據湖與數據中臺架構，規劃全院級的數據整合、ETL 流程與數據治理體系。 

4. 推動醫療數據標準化： 負責推動並落實 HL7/FHIR 等國際醫療資訊標準在系統中的應用與數據交換。 

5. 制定技術規範： 建立與推行開發、安全、部署、監控等方面的技術標準、規範與最佳實踐。 

6. 規劃 DevOps 體系： 設計 CI/CD 自動化流程與可觀測性（Observability）系統方案，提升交付效率與系統穩定性。 

7. 技術選型與評估： 負責核心技術元件（雲端服務、資料庫、中間件）的選型、評估與概念性驗證（PoC）。 

8. 解決方案與技術攻關： 領導團隊解決專案中的關鍵技術挑戰與架構瓶頸。 

9. 技術指導與審查： 提供技術指導與培訓，並負責核心程式碼與架構設計的審查（Review）。 

10. 前瞻技術研究： 持續引入雲端計算前沿技術，驅動醫療系統的架構創新。