測試平台軟體(資深)工程師(土城/新竹)

您將共同進行以下工作項目: 

1. HPC軟硬體集群架構規劃 

2. 網路系統設定與管理 

3. HPC 叢集建置與管理自動化

* 雲平台產品的售前與售後支持 

* 提供維運團隊技術支援 

* 對用戶需求做分析及提供解決作法 

* 對團隊內部及合作單位進行教育訓練

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

ATA 產品開發 

1. 負責通訊產品嵌入式系體軟軔體開發 

2. 負責產品後續維護、問題分析及除錯

1. FMCW, Chirp 雷達演算法開發  

2. DSP 訊號處理演算  

3. 硬體語言程式 

4. 因業務需求可能要出差或長駐海外

開發各種新世代寬頻通訊設備VoIP, ADSL, WLAN, Cable Modem, Ethernet、Home Lans, Internet Appliances, STB, WiMax, IP Phone, Video Phone, Smart Phone ....之軟體/韌體

Ethernet Switch Development : 

1. Linux related device drivers 

2. Linux Kernel/driver/BSP Porting and Integration 

3. BMC/IPMI related firmware

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

參與 5G/6G 通訊軟體開發與通訊協議測試。協助低軌衛星酬載之硬體整合驗證；配合團隊進行量子計算軟體實驗，支援智慧聯網架構的技術文檔彙整 。 

Participate in 5G/6G software development and protocol testing. Assist in satellite payload hardware integration. Support quantum software experiments and compile technical documentation for smart networking.

1. 參與高階網路交換機的硬體架構設計與系統規劃 

2. 設計並驗證 PCB 電路板，確保高速訊號完整性與可靠性 

3. 整合 ASIC/FPGA、SerDes、PHY 等高速晶片模組 

4. 開發與測試 100G/400G/800G Ethernet 介面及光模組整合 

5. 進行硬體 bring-up、功能驗證與效能測試 

6. 與韌體/軟體工程師合作，確保硬體與系統整合順暢 

7. 撰寫技術文件、測試報告，並支援量產與品質控管

1. 儲存器/伺服器系統整合測試及功能驗證 

2. 軟/軔體測試規劃與執行 

3. 客戶問題分析與驗證. 

4. 自動化測試程式開發 

5. 撰寫測試報告及擔任與客戶的溝通窗口.

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

負責ODM產品於開發過程中之設計品質監控、分析、確認與管理，確保產品設計階段符合品質標準與專案進度要求 

主要職責： 

1.參與新產品設計需求及規格問題的討論及改善對策 

2.協調及確認新產品驗證測試計劃和資料庫 

3.定期稽核研發部門設計審查執行情況 

4.DFMEA,PFMEA等問題彙總及跟蹤 

5.判定產品研發狀態是否符合進階門檻 

6.產品設計質量問題的跟蹤，督促和協調各部門解決問題的進度 

7.產品設計問題的客訴案件跟進

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。

(embedded Linux experience acceptable if no prior OpenBMC exposure). 

2.Implement and integrate low-level drivers (U-Boot, Device Tree, Kernel), covering I2C, SPI, PMBus, GPIO, and other interfaces. 

3.Build and maintain BMC sensor monitoring, FRU/SDR tables, fan/power control, and event log systems. 

4.Implement management protocols and firmware update mechanisms (IPMI, Redfish, PLDM, MCTP). 

5.Integrate Secure Boot / TPM / SPDM security frameworks. 

6.If experienced with NVIDIA HGX/DGX/NVSwitch projects, support GPU power/thermal control, firmware updates, and OOB management integration. 

7.Prepare design documents, test plans, mass production support materials, and debug reports.

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)

＜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. 與客戶溝通產品規格 

2. 分析測試單位提出的顯示器問題並且與客戶說明 

3. 產線指令撰寫 

4. 與廠商討論並解決測試單位的問題