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. 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. 結構強度模擬分析-DT/WS 2. 偕同不同function team合作進行驗證、分析與解決問題 3. 模擬新技術導入與研究 4. 模擬工具二次開發
1. 熱流模擬分析-DT/WS 2. 熱傳溫度測試-協助RD除錯-台灣 3. 跨部門function team合作進行驗證、分析與解決問題 4. 模擬新技術導入與研究 5. 模擬工具二次開發
主要負責: 路由器/交換機/服務器 1.NPI 產品生產過程中不良分析,找出產品設計bug,提供客戶改善建議。 2.量產異常分析,並協助CFT改善生產良率。 3.RMA/RCFA/ORT不良品失效分析,及時反饋產品問題並改善。 4.MRB不良物料失效分析,協助廠商分析推動零件良率改善。 5.3-Strike、疑難板及專案處理及分析。 6.產品技術資料整理及編寫 職務需求: 1. 電機電子、通訊工程相關科系專業 2. 2年以上失效分析相關經驗 ,熟悉半導體、電子元器件、電子電路領域的失效分析流程由家 3. 具備系統性思維,能通過實驗數據推導失效機理,熟悉FTA(故障樹分析)、8D、5Why等分析工具。 4. 熟悉路由器、交換機、伺服器等網路產品生產、測試及分析流程。 5. 熟練使用萬用表、示波器、頻譜分析儀等常用測量儀器測量相關電路及元件信號。
1. 主導企業級藍圖規劃與策略制定 2. 建立及維運架構治理與審核機制 3. 推動共性平台與技術資產建設 4. 引導企業技術發展與前瞻佈局 5. 培養組織架構人才與技術文化
1. 設計端對端解決方案與技術選型 2. 確保方案遵循企業標準與整合性 3. 主導關鍵技術驗證與風險評估 4. 提供專案開發的架構指導與支援 5. 沉澱專案經驗與促進技術交流
<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. 對於AI高階水冷工作站系統架構設計/接口定義感興趣 2. 負責物料開發及管理,確保開發流程順利 3. 制定系統測試與驗證計畫,追蹤及解決 issue 4. 跨部門協作與製程整合,處理 NPI 及量產階段的系統問題 5. 良好溝通能力與具客戶協作經驗
1. AI PC MCU韌體(Embedded Controller)/FreeRTOS 程式開發、更新、維護 2. AI PC MCU韌體(Embedded Controller)/FreeRTOS 研發時程及可行性評估 3. AI PC MCU韌體(Embedded Controller)/FreeRTOS 規格的review與分析 4. 專案執行與相關功能團隊合作 5. 良好的溝通協調能力 6. 具備產品分析與問題解決能力 7. 對工作具備熱誠 8. 具備邏輯思考能力與抗壓性
1. 指導並執行客戶端設備安裝、架設與維護 2. 負責現場需求溝通,協調並解決技術問題 3. 協助FAE團隊建置,並負責海外專案人力調配
We are seeking a software project manager to join our development team. In this role, you will be responsible for the following tasks: 1. Project Planning & Management - Define project plans, schedules, and resource allocation. - Track project progress to ensure on-time delivery and quality. - Identify risks and work with the team to resolve potential issues. 2.Cross-functional Coordination -Collaborate with development, QA, UI/UX, DevOps, and other teams. -Act as the bridge between clients, business stakeholders, and the engineering team. -Requirement Management 3.Gather, analyze, and confirm requirements, and draft Project Requirement Documents. -Help stakeholders define features and prioritize the product roadmap. -Quality, Delivery & Issue Tracking -Monitor milestones and deliverables to ensure quality standards. -Track bug issues, assign ownership, and follow up on resolution to ensure timely fixes and product reliability. 4.Reporting & Communication-Provide regular project status reports to leadership and stakeholders. -Perform system function demos to leadership and stakeholders to showcase progress. -Draft, review, and maintain user manuals and operational documentation to support end-users. 5.Administrative Support -Assist in internal administrative processes, including form creation and submission. -Handle expense applications and reimbursement requests. -Support supervisors with preparing presentations, documents, and reports. ## Requirements: - 5+ years of experience in software or technology companies. - 2+ years of experience as project or product manager. - TOEIC 800 or higher level. - Excellent communication skills in Mandarin and English. - Quick learner of new knowledge.
1. 負責雲端平台的架構設計與開發實現,支撐端雲一體化整合方案的技術落地,保障雲端系統與終端設備的高效協同及穩定運行。 2. 參與慢病管理平台、醫院HIS系統數據通道等基礎架構的雲端技術搭建,設計並實現FHIR協議數據互通的雲端解決方案,確保全場景數據流暢傳輸與交互。 3. 基於客戶需求,進行雲端系統的定制化開發與優化,參與解決方案及系統設計說明書中雲端部分的編寫,明確雲端應用與設備端產品的整合邏輯。 4. 與FAE、業務團隊協作,理解客戶在端雲項目各階段的雲端需求及問題,參與解決方案的討論與制定,跟進雲端功能的開發與交付進度。 5. 制定雲端平台的交付規格,明確技術標準與FHIR&DICOM協議接口規範,確保雲端系統交付符合客戶預期,同時配合項目團隊完成雲端部署的技術支持。 6. 編寫雲端開發相關的技術文件,包括微服務架構設計、接口說明、開發指南及TFDA相關資安文件,參與客戶的雲端解決方案簡報,根據反饋調整雲端技術方案。
Work with ID/MD/HW/SW team for Acoustic related design, testing, fine tune, certification, and customer acceptance; including RFQ review, Test plan buildup, ID/MD/HW/SW Design review (acoustic related items), Voice quality Verification, Voice quality fine tune, and MFG line test setup.
1. 製造系統管理:熟悉 MES、SAP 系統之基本架構與運作流程,並進行 MES 系統帳號管理、權限設定與日常維運。 2. 系統操作與分析:熟悉資料查詢與報表工具(SQL、Excel Power Query、Power BI 等)能針對生產數據進行分析,協助製程改善與決策支持。 3. 基礎程式撰寫能力:進行簡單系統調整或介接(Java / C# / Python 其中一種)。 3. 資料庫與備份:熟悉資料庫操作(Oracle / SQL Server),能撰寫查詢語法並進行資料維護,了解備份與還原流程,確保系統與資料完整性。
1.電子產品的硬體設計人員 2.開發產品設計審查、品質規劃、自動化流程設計 3.具硬體電子電路設計、電路分析與除錯經驗 4.熟悉善用Allego等設計軟體 5.具電子零件如MCU控制器,MOSFET,電感,電容,LDO等有相當認知
1.全球貨物流動/運輸保險的投續保、理賠、損害防阻推動及季度申報作業 2.海外新建或擴廠之工程相關保險之投保、理賠及損害防阻推動作業 3.其他主管指派之任務
1. 規劃及執行 AI Server or NB/Compute Node/GPU 等之系統整合測試。內容包含硬體/軟韌體/相容性/效能/産品功能等。 2. 產品品質問題追蹤、分析及改善。 3. 依照專案任務需求和客戶開會報告。
負責智慧城市企業用戶需求訪談、解決方案設計與專案管理,推動智慧城市專案落地 1. 熟悉B2B產品與解決方案設計 2. 具備跨部門溝通與需求訪談能力 3. 熟悉政府標案與大型企業客戶合作流程 4. 有智慧城市或數位轉型經驗尤佳
•架構設計與搭建:結合 HIS、EMR、PACS 等醫療系統需求,設計智慧醫院及機器人平台高可用資料庫架構;選型關係型 / 非關係型資料庫,搭建優化集群。 •數據集成與支持:參與數據中臺建設,完成 ETL 數據整合;支持開發團隊設計評審,為科室提供技術諮詢與培訓。 •安全與合規:管控數據訪問許可權,加密敏感醫療數據;配合審計與監管檢查,落實合規整改。 •日常運維與監控:負責資料庫實例、許可權、性能調優;搭建監控體系(CPU、IO 等指標);制定並執行備份恢復策略。 •技術迭代與應急:評估新技術(雲資料庫、分佈式等),制定升級遷移方案;制定應急預案,處置宕機、數據損壞等突發問題。