系統工程師 System Engineer-Sustaining

1.擔任 RD 與工廠端之間的技術橋梁，協調設計需求與量產／維修需求。  

2.熟悉 AI Server 工廠產線運作，協助處理量產導入、異常分析與改善追蹤。  

3.負責 DFI、DFS 與 FRU parts 客製需求 的規劃、確認與執行。  

4.處理並追蹤 ECN / ECR 相關變更流程，確保設計變更順利落地。  

5.與 RD、ME 密切合作，針對機構、零件、可維修性與服務性議題進行溝通協調。  

6.熟悉 Server 拆解、組裝、故障判讀與維修流程，可支援現場技術問題分析。  

7.負責 Service Manual 與相關技術文件之製作、更新與維護。  

8.協助建立與優化維修流程、FRU 更換方式及服務支援標準。  

9.支援新產品導入（NPI）與量產後技術問題的跨部門整合與推進。

Data Center Switch設計開發 

1. 資料中心交換機與DPU網路卡系統架構開發設計與硬體電子電路設計開發 

2. 產品測試驗證計畫執行與客戶認證 

3. 量產導入，處理產品良率分析與改善 

4. 跨部門團隊（PM/製造/品保）協作，確保產品品質與開發交付時程 

5. 協助客戶技術支援與問題排除 

6. 支援海外生產線(越南)相關測試設備架設與優化及自動化導入

1. New project RFx proposal 

2. PCA schematics & layout design and review. 

3. Issue debug and resolution provide 

4. New technology research and implementation. 

5. Timely support quality issue.

1. BU/Vendor Engagement & PCN Management 

•Coordinate in vendor’s component samples by BU’s requested for PCN validation. 

•BU validation status and schedule follow up, needs to ensure all PCN be closed on time. 

2. Documentation & Systems Support 

•Prepare and update component qualification reports by each project developing stage, supplier HW/FW changing records, internal CE checklists. 

•Maintain FEP component database accuracy. 

•Support uploading MRR, BOM and compliance certifications (CCF/CCD) in Agile. 

3. Technical support 

•Work closely with CEs and vendors for PTRR review to ensure FEP resilience. Also participate in CE/GSM/Vendor meetings and follow up on action items to ensure FEP readiness milestones are achieved. 

•Engage with CE and vendors for Component Life-Cycle management and 2nd source analysis by different CPNs.

負責產品：車載外包廠品質管理 

1.本地供應鏈含代工廠的開發、評估和稽核（VDA 6.3 +PPAP） 

2.新增Local 物料的承認測試 

3.供應鏈/代工廠的PCN變更所需要材料Qualify和PPAP稽核 

4.協助QA/PQE 對代工廠日常和年度稽核 

5.串接海外RD和生產製造單位，處理各類物料的FA和各種應急出差

* 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. 注塑或者鈑金件開發 

2. 生產製造 

3. 機構類產品NPI項目管理

＜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.與國際客戶溝通模治具功能與規格  

2.設計圖繪製並與加工單位檢討加工可行性  

3.利舊與功用性能評估 

4.成本與整體製程效益評估 

*需出差

1. 負責伺服器散熱元件開發(CDU,Manifold...)、水冷產品開發(EV、HPC)，需熟熱傳學、流體力學、材料力學與熱交換設計。 

2. 對高瓦數的水冷散熱的設計方案有基本了解。 

3. 對於焊接、沖壓、CNC等工藝之製程與機械加工有基本理解。 

4. 協助解決試產製造及製程中的相關問題。 

5. 繪製工程圖（2D&3DCreo, Solidwork），需有公差概念。 

6. 負責各產品工程技術文件之製作(DFM, DOE等相關技術報告) 

7. 完成其他主管交辦事項。

1. Familiar with rack-level liquid cooling system configuration (L-to-L / L-to-A) 

2. Experience on the cooling parts like Fan/pump/heatsink/cold plate 

3. Experience on CFM simulation tool and is plus 

4. Experience on facility cooling system / thermo-fluid test equipment design is plus

1. 針對客戶需求與供應商進行AI Server/Rack機櫃散熱設計(氣冷及液冷) 

2. 主導或參與液冷技術的導入，包括 CDU、manifold、coldplate和QD整合 

3. 積極與function team保持密切合作 ，確保系統能在高附載下穩定運作 

4. 量產前後與工廠和供應商檢討量產問題分析與問題改善

1. 設計伺服器硬體組件（如主板、CPU、IO卡），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. 支持製造和客服，診斷硬體故障，提供技術支援。 

4. 需要時與供應商溝通，處理設計相關的問題，確保產品品質。 

5. 替代料選用與BOM製作。

1. 負責筆記本電腦新產品導入之電子系統設計開發驗證,協助客戶完成板端和系統端之EE設計驗證並確保產品可量產化 

2. 執行失效分析(FA),SI/PI訊號量測與分析及DOE執行 

3. 撰寫英文技術報告,並與國際客戶進行溝通與合作

1.Hardware design proposal/specification  

2.Schematics design 

3.Level 6 E-BOM creation  

4.Board bring up and debug 

5.Power on Test plan & report  

6.Level 6 component selection 

7.Cost down plan & implementation  

8.EVT/DVT/PVT Failure Analysis 

9.OEM/ODM/IDM Design Review

CESBG 產品線: Server產品 硬體工程師 

1.硬體線路設計  

2.硬體設計審查和BOM產出  

3.審查 PCB Layout  

4.執行開機測試和執行除錯

CESBG 產品線:Server / Storage / Networking  

1. 硬體電路線路圖設計及佈線審查 

2. 硬體電路測試驗證、信號量測 

3. 協助工廠端進行試產測試 

4. 問題分析及解決方案能力

1.懸吊之避震器總成設計開發與規格制定、外包資源整合協調及供應鏈工程技術對接。 

2.懸吊之圈簧、板簧設計開發與規格制定、外包資源整合協調及供應鏈工程技術對接。 

3.懸吊之控制臂或拖曳臂、防傾桿設計開發與規格制定、外包資源整合協調及供應鏈工程技術對接。 

4.懸吊之鬆配件設計開發與規格制定、外包資源整合協調及供應鏈工程技術對接。 

5.懸吊系統之設計開發流程制定、工程規範及技術能量建置。

1. 大型連線自動化設備機構方案規劃和技術指導； 

2. 點膠雷射&貼膜組立等自動化設備機構方案評估及結構設計； 

3.點膠雷射及貼膜組立等設備的核心工藝實驗，驗證，及可行性報告產出； 

4. 現場設備的調試優化改善及異常處理 

5.機構標準化文件的制定與發行 

*須配合職務需求出差派駐

1.研發(量產)階段工廠端新機種機構問題收集、分析、追蹤及改善。  

2.產品機構材料問題的分析、處理及品質的改善。 

3.配合產品需求，進行治具(設備)的設計、開發、評估與規劃。 

4.產品設備的開發、導入、維護及改善。