於餐飲場所中,進行顧客服務、內外場聯繫、點餐供餐等工作。 1.負責餐飲場所的內外場聯繫、顧客菜單諮詢、點餐供餐及桌面環境清潔 2.協助廚師烹調前與烹調中的準備工作,與其它餐廳的相關事務 — 工作時段 — 10:00-22:00 分 早、晚、假日班,每個班別排班4-8小時 ※ 依營運需求彈性排班,工作時間面試詳洽 ※ 全台各營業據點: https://banjiouwoo.com/location/
加油服務 將汽油、柴油注入顧客的車輛油箱 替顧客結帳 提供洗車窗等加值服務 替顧客兌換贈品 營業時段結束時,進行會計出納對帳
櫃檯點單收銀、煮茶、現場吧台調茶、外送飲料、環境維護等店務 需具備機車駕照,無駕照者請勿投遞
身為門市人員,你將不只是店員,更是顧客專屬的運動穿搭顧問! 💪 你的日常任務: 品牌大使: 提供充滿熱情的顧客服務,分享最新的運動與潮流資訊。 門市營運: 協助商品進退貨、庫存管理、賣場視覺陳列及維持舒適的購物環境。 業績達標: 透過專業建議協助顧客挑選合適商品,與團隊一起挑戰銷售目標。 ✨ 為什麼要加入我們? 無經驗可: 提供完整新人培訓,學長姐手把手帶領,沒經驗也能快速上手! 團隊氛圍: 工作氣氛年輕活潑、溝通扁平,歡迎熱愛運動的你加入我們的大家庭。
身為門市人員,你將不只是店員,更是顧客專屬的運動穿搭顧問! 💪 你的日常任務: 品牌大使: 提供充滿熱情的顧客服務,分享最新的運動與潮流資訊。 門市營運: 協助商品進退貨、庫存管理、賣場視覺陳列及維持舒適的購物環境。 業績達標: 透過專業建議協助顧客挑選合適商品,與團隊一起挑戰銷售目標。 ✨ 為什麼要加入我們? 無經驗可: 提供完整新人培訓,學長姐手把手帶領,沒經驗也能快速上手! 團隊氛圍: 工作氣氛年輕活潑、溝通扁平,歡迎熱愛運動的你加入我們的大家庭。
櫃檯點單收銀、煮茶、現場吧台調茶、外送飲料、環境維護等店務 需具備機車駕照,無駕照者請勿投遞
櫃檯點單收銀、煮茶、現場吧台調茶、外送飲料、環境維護等店務 需具備機車駕照,無駕照者請勿投遞
工作內容 1.照顧失能或失智長輩 2.需備照顧服務員結訓證書或技術證 (可推介照服員就業獎勵) 3.工作地區:東區、南區、仁德區 工作內容 1.長輩日常生活照顧(含供餐、潔牙、午休等) 2.促進與協助長輩自我生活能力(運動、認知) 3.運用照服專業於長者日常或活動帶領 4.服務紀錄撰寫 5.配合主管交辦事項 徵才對象: 領有長照小卡 工作內容: 1、身體照顧服務: 包含協助沐浴、穿換衣服、協助餵食或管灌、修剪指(趾)甲、翻身拍背、肢體關節活動、 上下床服務等等... 2、家務及日常生活照顧服務: 換洗衣物洗滌、家務協助、備餐、代購、陪同外出或陪同就醫等等... 3、喘息服務、短照服務 免經驗可
1. 開發硬件上各接口測試程式(ex: CAN/SPI/I2C/GPIO/PWM/Ethernet/UART) 2. 規劃與撰寫測試計畫與測試案例 3. 測試與驗證系統功能、相容性、效能、壓力承載、可靠度等。 4. 建立測試環境,撰寫、維護、改善測試程式。 5. 分析測試資料、釐清問題、提出改善建議,並撰寫測試報告。 6. 產品生產測試流程規劃及導入 7. 撰寫使用手冊、安裝手冊或其他客戶支援相關文件 8. 有伺服器相關測試經驗者優先錄取
Job Summary/Role: The Big data developer team works closely with the manufacturing functions in all relative data fields, such as, 1) connecting and automating the data pipeline from MFG file servers, API, RDB, etc., 2) building structurally data warehouse and data market for flexible application or dashboard, and 3) also handling data cleansing and data governance. In order to accelerate the development of application/analysis, Big data developer will be the individual contributor with strong experience in the technologies of Big Data, Data warehouse, SQL and NoSQL etc. Also Big data developer will also work closely with data analysts/data scientists to solve the real MFG cases. Responsibility: • Collaborate with users, data analysts, data scientists to develop flowcharts, layouts and documents to identify solutions. • Architect on real MFG needs and translate requirements into technical needs. • Identify and understand the data sources that are relevant for analysis, and implement efficient data engineering functions (including data ingestion, cleaning, ETL, integration, etc.) • Consolidate the requirements and using data engineering skills to design a robust Data Mart. • Participate in design, architecture review and deployment of Big data and data warehouse solutions. • Design for automation and monitoring mechanism in a continuous integration environment. • Bring new data technology with POC to solve existing data challenges. • With high performance and comprehensive SQL to process data in relational databases (or Map/Reduce style querying for NoSQL databases). • Work closely with user/IT/data science team to design and develop scalable data pipeline or end-to-end analytical workflow. • Provide direction, training, and guidance to less experienced team members.
1. 硬體診斷軟體開發及現有模組維護 2. 硬體壓力測試軟體開發及維護 3. 依產品功能建構測試計畫並導入工廠
1. CI/Automation/Test Automation (Python) 2. Web Application (Python, Node.js, Java) 3. 網管系統或 BMC/Redfish related external system (Python, Linux shell) 4. AI, BigData, Datastore development (Python, Java)
1. 規劃伺服器及Rack Level產品自動化測試方案 2. 規劃及開發 Rack Level 自動化測試程式 3. 規劃及導入實驗室或工廠自動化測試 4. 規劃及開發客戶或實驗室需求的軟體工具 5. 協助研發單位規劃自動化測試需求
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. 研究雲平台核心元件和新功能、新版本開發演進,及系統優化,進行功能導入設計 2. 平台上層應用服務整合設計與開發 3. 協助平台問題釐清解決與設計優化 4. 平台架構設計與優化
1. 負責AI應用資料視覺化顯示與雲端顯示介面 2. 協助AI Framework雲端顯示介面開發 3. 持續學習新技術並導入相關系統開發
1.董事會及功能性委員事項 2.股東會年報/議事冊編制 3.關聯公司董事會/股務事務 4.重大訊息公告 5.董事會績效評鑑事宜 6.ESG例會G小組考核指標回覆
你會進入電動車的核心作業系統團隊,負責車內軟體的整體架構開發,提供車內軟體服務與控制系統整合執行框架,降低軟體開發的複雜度。你的工作內容包含: 1. 設計並開發車內軟體系統架構,確保能符合功能需求規範 2.建立模組化開發流程,促進各模組獨立開發 3.導入軟體工具,加速開發時程並降低複雜度 4.建立編譯與 CI/CD 系統,將各模組自動化整合編譯成為最終軟體映像 5.使用並熟悉整車軟體設計開發工具
你會進入電動車的核心作業系統團隊,負責開發各項車內軟體服務,透過網路讓車內主機相互溝通,傳遞控制命令與狀態訊號,並確保實時性與穩定性。你的工作內容包含: 1. 開發與維護車內軟體服務,進行功能開發 2. 參與軟體系統架構設計,定義車內通訊服務介面 3. 與底層軟體團隊合作,確保整體系統符合功能需求規範 4. 建立軟體設計規格文件 5. 使用並熟悉各項車用軟體開發工具
<About the job> As the AI Software Engineer, you‘ll join the various advanced Data Science & AI Projects in the corporate headquarters. As well as developing intelligent applications via related AI and Big Data Analytics Technology for digital transformation, you will have plenty of opportunities to develop emerging applications based on different use cases and expand your tech skillset in this world-class company (Fortune Global 500, 20th). <Job Description> Responsible for deploying the AI/Data Science collaborative framework and building the AI model and data operating infrastructure. Using software development experience to design and develop high-performance automated systems for AI development and operation. As below: .Collaborating with Data Scientist/AI ML Engineer team, other software system development teams, and the infrastructure team. .Ability to utilize various tools/methods to build the MLOps/DataOps/DevOps and deploy and manage the AI Development framework and infrastructure .Developing infrastructures for data transformation and ingestion and automating important infrastructure to process data .Deploy AI models to the Inference server and optimize the performance of the model serving operation reliably and efficiently. .Assist the Data Scientist/AI ML Engineer team in converting the AI models into APIs to serve other systems or integrate with other systems. <Skill Sets> (1)Excellent problem-solving and troubleshooting skills. (2)Genuine passion for learning new technologies and open-source projects. (3)Familiarity with Python and Java (python is a must) (4)Good understanding of the Linux OS environment, the Shell Scripting, and infrastructure/networking knowledge. (5)Experience with GitLab CI/CD (Nice to have but not necessary) (1)Experience with MLops and Model Serving tools. (2)Experience in GPU programming and performance tuning (3)Being familiar with AZURE (or AWS) cloud infrastructure will be a plus (4)Familiar with declarative infrastructure/container technologies, such as Docker and Kubernetes (k8s/k3s)