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職缺名稱公司名稱上班地點工作經驗更新薪資待遇
- 面議（經常性薪資達4萬元或以上） 新北市土城區 工作經歷不拘 1天前展開
1.研發(量產)階段工廠端新機種機構問題收集、分析、追蹤及改善。 2.產品機構材料問題的分析、處理及品質的改善。 3.配合產品需求，進行治具(設備)的設計、開發、評估與規劃。 4.產品設備的開發、導入、維護及改善。
- 月薪29500~35000元 嘉義市西區 工作經歷不拘 5天前展開
1.接受顧客詢問或主動提供諮商建議給顧客 2.陳列商品、清潔櫥窗、維持營業場所的整潔與美觀 3.向顧客說明貨品的性質、特徵、品質與價格 4.相關課程及組合產品的介紹 5.在當天結束營業前，統計銷售情形、盤點貨品存量及撰寫當日業務報表 6.具業務行銷經驗者佳！
績效獎金意外險員工聚餐尾牙員工在職教育訓練 - 面議（經常性薪資達4萬元或以上） 新竹市東區 工作經歷不拘 今天展開
1. 網通產品機構設計 2. 機構圖檔設計審查(包含干涉檢查、公差分析) 3.設計提案改善與設計驗證 4.生產問題解決和對策導入 5.各階段試產不良分析與改善
- 月薪33200~36200元 新北市五股區 工作經歷不拘 今天展開
1.協助照顧嬰幼兒生活起居 2.協助嬰幼兒建立生活常規，自理能力的培養 3.配合嬰幼兒發展狀況，提供多元適性教導方式，如:故事引導、教具操作、陪伴遊戲 4.照顧兒童其他日常生活事項 需相關科系畢業(幼保、護理、學前教育學系)， 或有保母證照。 歡迎幼保畢業者， 有耐心陪伴嬰幼兒的夥伴。 一同加入我們的工作行列!
三節獎金禮品績效獎金國內旅遊國外旅遊 - 時薪196~196元 新竹市北區 工作經歷不拘 4天前展開
門市職務說明： 1.麵包陳列上架 2.產品包裝、切片/切塊 3.收銀工作 4.現場顧客應對服務 5.店鋪環境、設備清潔維護
員工團保伙食津貼尾牙員工結婚補助生育補助 - 面議（經常性薪資達4萬元或以上） 新北市土城區 工作經歷不拘 1天前展開
1. 產品結構靜態強度分析 (產品組裝、卡扣強度模擬) 2. 產品結構動態強度分析 (落下、衝擊模擬) 3. 跨部門討論並解決產品結構問題 4. 結構分析結果報告之撰寫
- 1111南台灣職場小語
徵【助理】無經驗可、週休二日/固定休六日
- 時薪196~196元 新竹市北區 工作經歷不拘 4天前展開
門市職務說明： 1.麵包陳列上架 2.產品包裝、切片/切塊 3.收銀工作 4.現場顧客應對服務 5.店鋪環境、設備清潔維護
員工團保伙食津貼尾牙員工結婚補助生育補助 - 月薪29500元 台北市中山區 工作經歷不拘 3天前展開
◆文件整理及資料輸入 ◆協助製作送審資料 ◆文書處理及檔案管理(含合約文件與圖說建檔、廠商資料歸檔、建材歸類樣本資料建檔) 根據需求人員提出之需求做採購 ◆聯絡廠商及追蹤進度、廠商資料維護及管理，並與良好廠商維持良好關係 ◆協助合約製作、簽訂用印及整理 ◆工程採購發包，詢價、比價、議價作業，廠商蒐集，找尋品質好、成本低、配合度高之廠商提供選擇 ◆各項呈核案件進度追踪，掃描建檔，登錄結案 ◆完成主管交辦事項
禮品產假產檢假全勤獎金年終獎金 - 月薪45000~60000元 新北市土城區 工作經歷不拘 今天展開
1.設計與最佳化電子產品組裝流程 2.SOP編寫與規格制定 3.產品組裝治具設計與驗證 4.導入半自動或全自動設備至組裝流程 5.協助客戶分析組裝/設計問題
- 年薪1000000元 亞洲其它 工作經歷不拘 2天前展開
1.設計與最佳化電子產品組裝流程 2.SOP編寫與規格制定 3.產品組裝治具設計討論與驗證 4.導入半自動或全自動設備至組裝流程 5.協助客戶分析組裝/設計問題
- 面議（經常性薪資達4萬元或以上） 新北市土城區 工作經歷不拘 1天前展開
＜About the job＞ As the Senior Data Engineer or Data Architect, 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＞ *Type 1：Senior Data Engineer Responsible for acquiring data using API, Web scraping, or other data accessing protocol/scripting and developing the ETL data pipelines, and the data aggregation systems. Using software development experience to design and build high-performance automated systems. As below: 1. Data Processing (1)Data ETL(Extracting/Transforming/Loading) process engineering and querying from relational data management(such as SQL Script). (2)Building systematic data quality processes and checks to ensure data quality and accuracy. (3)Solid coding experience in Python or Java. 2. Data Pipeline Development (1)Develops a data integration process, including creating scalable data pipelines and building out data services/data APIs. (2)Create a data processing automation and monitoring mechanism by optimizing the data pipeline process. (3)Experience with dataflow/workflow/management tools, such as Apache Nifi, Apache Airflow, Azkaban, etc., is preferred. 3. Data Crawling (1)Build scalable tools that automate web crawling, scraping, and data aggregation from various web pages using frameworks such as Scrapy. (2)Accessing data from REST APIs, particularly in parsing data in disparate formats such as JSON and XML, and developing automated engineering. (3) (Nice to Have) Knowledge of server-based front-end/UI technologies, including Vue/React and HTML/CSS, is preferred. *Type 2：Data Architect Responsible for designing, implementing, and maintaining scalable and reusable system architectures/data architectures for complex data structures and large data in data science and AI projects. As below: 1. Data Schema Design (1)Collaborate with the team to design DB/Table Schema and Data Schema. (2)Consolidate the requirements and use data engineering tech to design and implement a robust Data Mart. (3)Experience handling all kinds of structured/semi-structured/unstructured data and streaming data is preferred. (4)Hands-on experience with Dimensional Data Modeling(Column-based data warehouse) or NoSQL Schema design. 2. Data Platform Architecture (1)Design and build data infrastructure/platform components to support complex data pipelines ingesting various data from multiple internal and external data sources and processing. (2)Familiar with Big Data frameworks and processing technologies, ex: Hadoop, Apache Spark, NoSQL ...etc. (3)Familiar with AZURE or AWS cloud data services(hands-on experience with cloud infrastructure will be a plus) (4)Familiarity with the Linux OS environment, the Shell Scripting, and infrastructure knowledge. (5)(Nice to Have)Experience with declarative infrastructure/container technologies, such as Docker and Kubernetes (k8s/k3s). (Nice to Have).
- 面議（經常性薪資達4萬元或以上） 新北市土城區 工作經歷不拘 今天展開
1. 了解使用者需求，主要負責PLM系統的導入，實施，配置。 2.使用Windchill軟件，利用PLM標準解決方案，根據業務需求，完成PLM產品需求定義，解決方案編寫及產品實現。 3. 負責PLM系統軟件設計，開發過程中相關文檔的主導和編寫。 4. 根據PLM系統部署和性能的情況，進行有效的代碼優化和系統性能調優等IT維護工作。 5.熟悉PLM全文搜索引擎，為文件和代碼使用加載文件進行部署 6.完成異構系統集成，如CAD,Creo等
- 面議（經常性薪資達4萬元或以上） 高雄市前鎮區 工作經歷不拘 今天展開
Job Summary: • The engineers should have comprehensive knowledge of AI Large language models, such as GPT-4, and their underlying mechanisms, including an understanding of natural language processing, machine learning, and neural networks. Key Responsibilities: • Construct, train, and fine-tune large language models to meet specific organizational requirements and goals. Implement strategies for AIGC to create high-quality content. • Integrate AI technologies into existing products and services, ensuring they align with business objectives and enhance user experience. • Work collaboratively with cross-functional teams and provide technical guidance to non-technical members. Stay updated with AI advancements and educate team members on new developments. • Continuously monitor the performance of AI models, making adjustments and improvements based on data analysis and business needs. • Maintain effective communication with other teams to ensure collaborative project success. • Engage in ongoing learning and research to identify and implement new and appropriate Large Language Model technologies to enhance overall efficiency.
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