【SW】I-軟體開發工程師

1. 伺服器BMC韌體設計開發 

2. 既有專案維護 

3. 跨單位技術上的溝通探討 

4. 了解客戶需求與熟悉產品規格

1. Embedded Linux development on ARM/MIPS SOCs.  

2. Linux technology and GNU tool chains. 

3. Experience of developing device drivers or kernel modules.  

4. Cloud Server, Storage Server, Data Center Server & Micro Server firmware development.

1. Lead the lead of firmware team for server project.  

2. Study technical issue for project‘s needs. 

3. Review & sign off requirement specification. 

4. Review engineer design. 

5. Review function/interface specification. 

6. Review bug fixing. 

7. Help the design and review the common definitions for debugging and profiling.

1. 熟悉微服務平台建置、維護與管理 (Kubernetes(K8S)、Docker)  

2. 經營/維護/優化 DevOps 工具 

3. Jenkins等 持續整合/建置環境建置與維護(CI/CD)  

4. Google Test 經驗 

5. 測試報告追蹤 

6. 可自主建立已上流程系統(必要).

＜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. 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

1. 使用者介面開發： 負責開發高品質、高效能、響應式的醫療系統前端應用程式與操作介面。 

2. 組件化架構實踐： 設計、開發並維護可複用、可擴展的標準化前端組件庫。 

3. API 數據串接： 與後端團隊協作，串接 RESTful API 或 GraphQL 接口，實現前後端數據交互。 

4. 應用程式狀態管理： 負責複雜前端應用的狀態管理機制設計與實現（如 Redux, Zustand）。 

5. 前端效能優化： 分析並優化應用的載入、渲染與運行效能，提升使用者體驗。 

6. 確保程式碼品質： 撰寫單元測試、組件測試與端到端測試，並參與程式碼審查（Code Review）。 

7. 前端工程化建設： 維護專案的建構工具鏈（Webpack/Vite）與 CI/CD 流程。 

8. 瀏覽器兼容性與調適： 確保應用在主流瀏覽器與不同設備上的兼容性與一致性。 

9. 跨團隊協作： 與 UI/UX 設計師、產品經理、後端工程師緊密合作，將產品需求高效落地。

＜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.