轉職熱搜工作

＜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. Design, deploy and maintain large scale AI/HPC cluster virtualization environment (Slurm, Kubernetes, Kuberay, Ray, Helm, HTCondor, LSF, DLRover, LamaFacotry, etc) 2. Orchestra and optimize large scale virtualization enivronment for HA and high performance 3. Security assessment and implementation on the large scale cluster platform 4. Scaling and automation system development

1. At least 5 years of experience in embedded system, FreeRTOS is a plus 2. Familiar with C/C++, Linux, TCP/IP, Streaming 3. Familiar with Reatlek, OmniVision, Sigmastar, Rockchip, Ambarella, Hisilicon or any IP camera platform. 4. Excellent troubleshooting and problem-solving skills. 5. Well communicate with different team such as Hardware, Audio, Optical, IQ, DQA, customer, etc. 6. Familiar with Git control tool

負責測試智慧城市應用之功能、效能與安全性，建立自動化測試流程與品質驗證標準 1. 熟悉自動化測試框架（如Selenium、Cypress） 2. 具備CI/CD下測試流程設計經驗 3. 熟悉API測試與效能測試工具 4. 能撰寫測試計畫與測試案例

加入全球指標外商，長期獲選「全球最理想雇主」、「最具吸引力科技企業」之《Fortune Global 500》龍頭設計團隊，實戰參與90至22nm HV 專案，無需英文門檻，進入國際工程圈。 【職務內容】 ˙需具備HV經驗 ˙需具備3-5年Driver相關經驗 ˙需熟悉繞線（Routing） ˙Block-Level設計經驗可 ˙能讀懂 Calibre DRC command file 語法佳 ˙具備28/22nm HV製程經驗佳 ˙無需英文能力，全台灣團隊

1.客製自動化設備控制軟體之分析、設計以及程式撰寫。 2.規劃執行軟體架構及模組之設計，並控管軟體設計進度。 3.進行軟體之測試與修改。 4.規劃、執行與維護量產的產品。 5.協助研發軟體新技術與新工具。 6.安裝與測試(設備交付)。 7.專案運營管理與績效考核。

1.設計整體平台架構，軟體解決方案以及應用程式的高階設計。 2.設計、實施並支持複雜的技術基礎設施解決方案，包括雲運算以及網路。 3.能與客戶、產品經理和開發團隊合作，了解所要解決的問題，作為技術架構設計的範疇。 4.指導開發團隊，進行代碼審查以確保符合設計標準。

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

We are seeking a highly motivated Software Engineer, who support the development, integration, and maintenance of the AI-driven software platform used in GPU server manufacturing and diagnostics. This role focuses on log processing, service development, model implementation, data analysis, and integration testing. The engineer will work closely with team members to implement features that improve failure attribution, test optimization, and automated diagnostics for AI server platforms. **Responsibilities 1. Software System Development Implement backend service modules for the system. Develop log parsing tools, data transformers, LLM, and rule-based diagnostic logic. Write clean, maintainable code (primarily Python) and participate in code reviews. 2. Log & Data Handling Build and maintain scripts for collecting, cleaning, and indexing diagnostic logs. Manage log storage and retrieving data for model training. 3. System Integration & Testing Support integration between the platform modules and Diagnostics software, automation frameworks, and factory systems. Help deploy updated components to test environments or production lines. 4. Issue Investigation Work with senior engineers to analyze failure logs, detect patterns, and refine rule-based logic. Document root causes and support continuous improvement of diagnostics accuracy. 5. Documentation & Team Collaboration.

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.