Application Engineer(工程師/主管)

(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.電路板開發、産品電路設計、PCB布局審核、産品測試除錯、硬體與機構成本分析 

2.負責EMC測試、修改與報告 

3.與硬體及機構工程師合作進行跨部門合作協調 

4.與客戶溝通協調，協助客戶解決EMC相關問題

•開發和維護EDA應用雲服務 

•使用Python和Git進行開發和版本管理  

•利用Python和資料結構及Algorithm進行資料處理分析  

•開發和維護Dash Web/Restful API  

•使用Yolo8和sentence-transformer進行finetune應用  

•使用OpenCV進行圖像處理應用  

•使用LLM/ VLM進行語言模型應用

CESBG-產品線Server 

1. 伺服器BIOS軟體開發及維護 

2. 客戶規格審閱 

3. 專案問題分析及解決 

1.BIOS development engineering feasility estimation  

2.BIOS product specification definition  

3.BIOS engineering specification creation  

4.BIOS development  

5.BIOS debug and mantainance

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

1.BIOS development engineering facility estimation  

2.BIOS product specification definition  

3.BIOS engineering specification creation  

4.BIOS development  

5.BIOS debug and maintenance 

1. 開發、維護以及改善主機板BIOS程式。 

2. 導入主機板相關零件控制方法。 

3. 負責BIOS程式偵錯與問題解決。 

4. 回覆客戶或相關部門BIOS技術問題。

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