高薪工作機會

工作內容：1. Lead the PM team, covering both NPI and sustaining projects. 2. Take lead projects from RFQ through NPI and MP stages until end of life. 3. Forecast/demand tracking, capacity, material preparation, and resource planning. 4. Manage AVL and ECN monitoring and implementation. 5. Conduct project risk analysis and resolve issues. 6. Drive cost management and cost reduction initiatives. 7. Coordinate with customers on NPI and MP project status as well as shipping plans.

工作內容：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.

工作內容：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

工作內容：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

工作內容：1.工程規劃：負責建廠評估、規劃設計、設計審查與工程預算編列及審查。 2.工程管理：執行材料品質管控、施工順序安排、現場協調、工期掌控與安全監督。 3.工程驗收：辦理測試與完工驗收，並完成工程內外部移交程序。 4.系統整合：主導五大系統及HVAC的設計與施工規劃，確保系統整合與穩定運行。 5.營運維護： 建立MEP系統點檢與維護計畫，確保設備長期穩定運行並持續優化。 6.跨部門協作： 協調設計單位、承攬商及業主團隊，確保工程執行符合需求與進度。 7.合規永續： 確保設計與施工符合當地法規、ESG與綠色建築標準，並導入節能改善措施。 8.海外支援：能接受海外出差與長短期外派。

工作內容：1. 國際永續評鑑與資訊揭露優化推動。 2. 供應鏈夥伴永續推動。 3. 協助拓展海外地區ESG 業務。 4. 協助ESG 公協會對接及合作推動。 5. 永續活動整合規劃。

工作內容：1. 具備Python基本能力，並熟悉版本管理知識及Git操作 2. 熟悉Python語言，並熟練運用dataclasses/concurrency/messaging/Flask/Dash，以及進行PDF注釋與Word/Excel讀寫 3. 熟悉LLM、Multimodal Model、Agent原理，能夠針對用戶需求，規劃與建置專屬應用(工作項包含但不限於:資料工程、prompt engineering、RAG、fine-tuing) 4. 熟悉NLP、字串相似度知識及演算法，能夠操作相關工具達成需求 5. 熟悉計算機視覺知識及演算法，能夠操作OpenCV等工具達成需求 6. 使用shapely、maplotlib進行幾何操作，包含:空間索引和查詢 7. 操作OrCAD、Allegro進行硬體組件、原理圖及PCB佈局設計 8. 熟悉設計模式及編程觀念，能夠撰寫需求分析及系統設計文件

工作內容：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

工作內容：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

工作內容：＜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.