1.主導公司人形機器人技術發展之藍圖與策略規劃，實現系統研發與產品落地。 2.帶領團隊開展人形機器人核心技術，涵蓋運動控制、機械結構設計、感知系統、人工智慧、語音交互、仿生演算法與人機協作技術等。 3.整合軟硬體、電控與演算法等跨領域團隊，推動專案從技術驗證至產品化的全週期執行。 4.結合市場趨勢與公司策略，制定技術演進路線與階段性目標，確保產品具備商業可行性與技術領先性。 5.參與高層技術決策，定期向管理層彙報專案進展及風險控制方案。 6.推動技術引進與資源整合，拓展學界、業界及供應鏈等合作夥伴關係。

1.負責人形機器人專案規劃至產品交付全流程。 2.主導專案目標設定、時程規劃與資源配置，推動原型開發至產品化。 3.協調軟硬體研發團隊，包括結構、控制/感知系統、演算法與嵌入式系統等，確保技術方向與專案目標一致。 4.建立標準化流程，優化團隊協作與開發效率，提升交付品質。

1. 熟悉自然語言處理 (NLP)，讓機器人可進行語音辨識、情感識別 2. 熟悉機器學習、強化學習等AI訓練，給予機器人決策、行為生成能力

1. Product test plan and test producedure building. 2. Generate test report 3. Generate release note. 4. Collaborate with HW/SW/ME etc. team.

1,對維修區整體KPI負總責; 2.維修Attrition Cost管控; 3.維修OPE達成管控; 4.維修人力及產能規劃與達成.

1.綜合辦理公司內之設備維護包含水電以及辦公用品修護 2.辦公室環境維護、清潔管理 3.交通、伙食供應管理 4.執行辦公室租賃之事務 5.各項請款作業 6.協助各部門處理庶務性工作

1.獨立負責專案 PCB Layout Placement，Routing與Gerber out。 2.協助解決產品開發階段PCB廠,PCA廠生產問題。 3.專案Placement及走線評估。

• 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. 統籌台灣專案採購事宜 2. 供應商及料件管理 3. 新專案sourcing廠商及詢價比價 4. 季度costdwon 5. 交期跟進處理 6. 異常處理

1.AI HPC系統散熱設計及驗證 2.系統噪音評估/設計及驗證 3.系統散熱模擬 4.水冷系統、散熱模組及風扇規格定義及設計 5.創新設計及新技術導入

1.統籌臺灣全域通關運營，制定高效合規的報關解決方案。 2.制定臺灣關務SOP，推動關務系統數位化升級，優化稅費成本並實施合法稅優方案。 3.構建臺灣關務合規與風控體系，主導內審及風險整改，確保業務合規有效性。 4.研判臺灣海關政策與貿易法規變化，評估業務影響並制定應對策略。 5.建立並維護與臺灣各級海關及政府高層的戰略關係，推進AEO認證管理。 6.搭建臺灣關務團隊與績效管理，協同內外部部門提供決策級合規支援。

＜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.

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. 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。

1.客戶專案管理-專案之整體規劃與進度管理，確保如期如質完成 2.顯示器產品開發-參與顯示器產品之開發流程，含驗證與導入量產等 3.成本評估分析-產品成本評估與分析，優化成本結構與提升效益

1.公司融資籌措，資金調度管理，銀行額度管理 2.公司外匯避險管理 3.公司預算編制及管控 4.海外子公司財務及資金管理事宜

1. 負責制定/執行量測儀器校驗計畫，包含：外校聯繫、內校建立等 2. 負責主導/執行品質管理系統和生產過程中所需的確效文件，包含：製程設備、檢驗儀器、電腦化系統等 3. 負責制定/監督關鍵製程和製程偏差，推動改善計畫並追蹤效果 4. 負責制定/撰寫原材料、過程產品、最終產品的檢驗規範與允收標準，監控供應商來料品質 5. 負責檢驗/追蹤重工和維修產品，並組織技術人員對重工產品進行根因分析 6. 協助執行/撰寫生產過程中的檢驗文件，包含：IQC/IPQC/FQC/OQC (兼QC職務) 7. 完成主管交辦事項

Key Responsibilities: • Assist internal & external customers with various administrative tasks directly related to NPI or sustaining enterprise server project. • Assist with materials preparation, testing sample arrangements, and logistical support among factories, vendors and R&D teams. • Provides development support for project communications, including creating status reports and summaries, maintaining trackers, coordinating stakeholder meetings. • Develops relationships with internal, cross organizational project teams for product development and manufacturing.

【共通核心職責】 負責 AI Data Center 專案之整體採購策略制定與落實，精準控管專案預算並達成降本目標。 供應商/工程顧問等開發、評鑑與管理，主導高階商務談判（包含價格、付款條件、優化工程服務契約與器材訂單）。 供應鏈風險控管與異常處理，解決遲交問題並提報，確保器材按時出貨或工程專案如期交付。 須配合專案任務與跟催廠商製造進度需求出差。 【領域 A：AI Server (ODM) 採購】 負責 AI 伺服器及相關 IT 設備之專案採購與 ODM 代工廠管理。 主導 RFX 選型選料、NPI (新產品導入) 報價與成本分析。 執行 BOM 表成本優化與 2nd source (第二供應商) 導入，降低整體物料與製造成本，機動執行交期 Pull-in，滿足工廠生產需求。 【領域 B：基礎設施 (Power/HVAC/EPC) 採購】 負責 AI 資料中心之 EPC 總承包工程發包、採購與分包商管理。 主導關鍵模組化機電設備（電力系統 Power、暖通空調 HVAC）之規格評估、詢議價與採購作業。 協調工程進度與重型設備交期，配合案場現場需求進行材料控管與施工異常排除。

1.Server BMC 功能開發/除錯/驗證 2.配合硬體及工廠解決問題 3.支援客戶BMC特殊規格需求更新