EMC工程師

* 負責雲端Server伺服器的相關工作 

1. 協助硬體部門專案測試及報告撰寫  

2. 協助部門處理庶務事項 

• 計畫介紹：  

• 實習期間: 即日起-2027/6 (長期實習) 

• 職缺內容: 實習生 (電子相關科系佳) 

• 實習薪資: 時薪(一週3天以上)，優於基本工資 

※完整一年期滿轉正過試用期另外有奬金哦~~

1.主導 AIDC 軟硬體整合架構設計，涵蓋 IT/OT 硬件設施與 AI DCIM 軟件，確保硬件與軟件有機結合、滿足 AIDC 整體需求目標。 

2.負責建構 AIDC 整合測試體系，定義功能測試、性能測試、壓力測試、容錯測試、安全測試、合規測試的策略與流程，建立測試指標體系。 

3.組織 IT/OT/軟件團隊/供應商共同執行 系統級整合測試，推動缺陷追蹤、根因分析與修復閉環。 

4.主導與用戶的 UAT 測試，確保交付滿足功能性需求、與非功能性需求。 

5.分析測試數據，發現系統瓶頸，提出改善建議並推動對應團隊持續優化。

1. 使用 VHDL/Verilog 進行 CPLD 電路邏輯開發。 

2. 執行模擬、合成與晶片燒錄，並進行 Debug。 

3. 設計 I²C、SPI、UART 等數位介面，與硬體電路整合。 

4. 確保設計符合時序需求，並優化資源與功耗。 

5. 產出設計規格書/測試報告，並與韌體、製造團隊協同作業。

1.負責伺服器電源時序效率測量與計算。 

2.負責伺服器電源輸入、輸出、反饋、保護電路電氣特性量測。 

3.負責伺服器電源單體可靠性保障。 

4.負責伺服器電源電路與電子零件應力分析與計算;電子零件應力測試;WCEPTA容差分析;異常分析與處理回饋;協助FA 

5.負責伺服器電源功耗量測與計算分析，電源兼容性量測。

＜About the Job＞ 

We are looking for a highly motivated and skilled AI Infrastructure Engineer with strong hands-on experience in Kubernetes (K8s), particularly in supporting AI/ML workflows. In this role, you will be instrumental in designing, implementing, and maintaining robust, scalable, and high-performance Kubernetes-based infrastructure that supports the entire lifecycle of our AI applications—from data processing and model training to deployment and monitoring. You will work closely with data scientists, AI/ML engineers, and DevOps teams to ensure seamless integration of AI/ML workloads within cloud-native environments. The ideal candidate has a deep understanding of container orchestration, distributed systems, and MLOps practices, and is passionate about building efficient, reliable platforms that enable rapid AI innovation. This is a unique opportunity to work at the intersection of AI and cloud infrastructure, contributing to next-generation systems that power intelligent applications at scale. 

＜Job Responsibilities＞ 

．Design & Architecture: Design, build, and scale a reliable and efficient Kubernetes platform optimized for AI/ML workloads. This includes provisioning GPUs, managing resources, and ensuring optimal performance for computationally intensive tasks. 

．Infrastructure Management: Manage the entire Kubernetes cluster lifecycle—from provisioning and configuration to ongoing maintenance, monitoring, and troubleshooting, ensuring high availability and scalability. 

．Deployment & Automation: Develop and implement CI/CD pipelines to automate the deployment, scaling, and updating of machine learning models and AI services. Ensure seamless integration with AI tools like Kubeflow, MLflow, and Argo Workflows. 

．Performance Optimization: Continuously monitor and optimize system performance, focusing on resource utilization, latency reduction, and improving the overall efficiency of AI workloads. Ensure high availability and minimal downtime for AI services. 

．Collaboration & Guidance: Work closely with data scientists, ML engineers, and cross-functional teams to understand their infrastructure requirements and provide technical solutions to meet workload demands effectively. 

．Security & Compliance: Implement best practices for cluster security, including network policies, access controls, and vulnerability management to safeguard sensitive data and maintain compliance. 

．Cost & Resource Efficiency: Manage resources effectively to optimize cost while maintaining high-performance infrastructure for AI model training, inference, and data processing. 

＜Skills & Qualifications＞ 

．Kubernetes Expertise: You should have hands-on experience with Kubernetes (K8s) architecture, including deploying applications, managing resources, and troubleshooting complex cluster issues in a production environment. 

．Containerization & Linux Environment: Strong knowledge of container technologies such as Docker, along with hands-on experience in Linux environments. Expertise in container orchestration and deployment practices is highly valued. 

．AI Workloads: Deep understanding of GPU scheduling and performance optimization, including strategies for resource allocation, workload balancing, and maximizing throughput for AI/ML tasks. 

．Automation & CI/CD: You need practical experience with building and managing CI/CD pipelines using tools like GitLab CI, Jenkins, GitHub Actions, or ArgoCD to automate deployments. 

．Programming & Scripting: Proficiency in at least one scripting language (e.g., Python, Bash) is a must. 

．Networking: Knowledge of container networking and service mesh technologies (e.g., Istio, Linkerd) is highly desirable and a great advantage.

1. DT/ WKS硬體電路設計，使用CAD軟體開發電路圖。 

2. 進行硬體原型測試，執行功率和性能基準測試，優化設計。 

3. 從設計分析確認Design Quality,處理設計相關的問題，確保產品品質。 

4. 診斷硬體故障，提供技術支援。 

5. 新技術研究開發與導入

1.系統設計開發人員 

2.系統開發可行性評估、系統DFX檢查、系統排線繞線定義、定制系統需求規格書 

3.精通英文、溝通協調能力

1、電路圖Design review  

2、Layout review  

3、設計驗證 Singal Integrity & Power Integrity  

4、主板失效分析和設計優化  

5、系統失效分析及設計優化

1.電路設計與開發：負責數位與類比電路的設計，包括電路圖開發與驗證，與PCB Layout review。 

2.元件選型與評估：選擇合適的電子零組件，並進行可靠性與性能評估。 

3.產品打樣與除錯：組裝與測試樣品，分析與排除電路異常或性能問題。 

4.硬體驗證與測試：撰寫測試計劃，使用示波器、邏輯分析儀等儀器進行功能與穩定性測試。 

5.協同跨部門合作：與韌體、機構、製造及品保部門密切合作，確保產品整體開發進度與品質。 

6.撰寫技術文件：完成設計報告、BOM 表、測試報告及其他相關技術文件。 

7.新技術導入：持續追蹤硬體技術趨勢，導入新技術以提升產品競爭力。

電動車類/車用電子/儲能 

1.BMS/BMU 硬體電路設計 

2.產品測試驗證及除錯 

3.產品故障分析及8D報告撰寫  

4.協助產線測試規劃及工廠生產現場支持，不良板問題分析 

5. BMS客戶問題溝通及現場技術支援

• Security Audits & Compliance: Execute internal and external audits, including documentation reviews, on-site audits, and vendor audits. 

• Risk Monitoring & Incident Response: Monitor security risks such as theft and unauthorized access. Assist in investigations and support corrective actions to prevent recurrence. 

• Client Project Support: Assist in implementing security plans for key customer projects. 

• Develop and update various security related documents (i.e., SOPs, policies, checklists, etc.). 

• Employee Training & Awareness: Develop, update, and support the delivery of physical security training programs focused on security awareness, theft prevention, access control, and emergency response. 

• Carry out other security-related tasks assigned by management

1. 產品線路設計 

2. 產品 PCB佈局設計 

3. 生產 BOM發行 

4. 零件評估選用 

5. 產品功能性驗證, 製作測試報告 

6. 產品 issue 分析 debug 

7. Design study and Design proposal

1. 機器人系統之電控元件選型評估與整合 

2. 規劃與設計電氣佈線架構 

3. 製作相關電路圖與接線圖

1. 維護量產後的伺服器產品相關文件(組裝文件, Label spec、BOM...) 

2. 發起工程變更通知(ECR)，優化伺服器設計與導入替代料 

3. 協助追蹤與解決量產後的系統問題與品質異常 

************************************** 

1. Maintain the customer and internal BOMs, as well as related documents (e.g., cable routing, assembly guidelines, label specs). 

2. Initiate Engineering Change Requests (ECR) to optimize server design and manage second source qualification. 

3. Tracking and resolving system issues and quality abnormalities post mass production.

1.組織日常運營管理: 組織建設、培訓、工作佈達及考核, 確保工作按照規劃100％完成 

2.人力需求評估與規劃, 招募評估及風險因應, 人員管理及KPI提升改善 

3.負責新產品試產方案評估、驗證規劃、新設計驗證改善 

4.維修分析團隊建設，人力佈局與Local接班梯隊培養 

5.維修方法驗證導入與良率提升改善

1.產品工站規劃與執行 

2.工站建立,校驗及故障排除維修 

3.產品功能可靠度評估

1. 數據中心IT架構規劃 

2. 冷凍空調、電源配置規劃 

3. 確認終端客戶IT需求

- 推動跨系統和模塊的集成，解決架構相關技術問題 

- 架構設計: 設計Genesis Store 架構模塊並與IT/OT組件集成 

- 與開發團隊保持密切溝通交流，設置檢查要求和節點，推動用例標準化 

- 生態合作對接: 確定IT/OT架構與生態解決方案之間的一致性和匹配性 

- 知識庫與Token*相關的系統建設: 負責相關的系統設計與建設 (如: 知識管理、Token*管理) 

*Token: 透過GenAI技術整合各種跨事業群的生產相關資料，如: 語句、圖像後的數據單位，有助在不同場景下訓練AI引擎

- 設計AI平台的技術架構 

- 優化模型管理、語料處理和監控工具，保障平台的高效運行和穩定性 

- 協助整合第三方成熟產品完成客製化需求

* 負責雲端Server伺服器的相關工作 

1. MB VR testing  

2. Schematics drawing 

3. brd file checking 

4. Create Test plan  

• 計畫介紹：  

• 實習期間: 即日起-2027/6 (長期實習) 

• 職缺內容: 實習生 (電子相關科系佳) 

• 實習薪資: 時薪(一週3天以上)，優於基本工資 

※完整一年期滿轉正過試用期另外有奬金哦~~