轉職熱搜工作

1. 自動化設備導入與開發：依據產線需求，規劃自動化方案，設計與執行自動化流程改善計畫。 2. PLC 控制程式設計與除錯，進行邏輯控制程式撰寫與優化。 3. 介面設計：負責人機介面開發與整合，提升操作效率與可視化監控。 4. 機器人與電控整合：整合工業機器人與周邊控制系統，包含運動規劃、通訊協定設計與參數設定。 5. 自動化設備智慧化開發：導入感測器與邊緣運算(Edge Computing)技術，提升設備預測維護與數據應用能力。 6. 設備現場安裝與測試：負責設備佈線、電控配盤、現場組裝與試車調適，協助量產導入。 7. 專案文件與技術資料編寫：撰寫規格書、操作手冊與維修保養指引，確保技術知識文件化。 8. 協助推動產線精實改善與自動化提案。 9. 主管交辦事項與跨部門技術支援。

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.

【工作內容】 1. 軟體工程系統開發 2. 自動化控制系統整合 3. 協助產線自動化系統推展 【工作班制】 ．班別：週一至週五，週休二日 ．時間：08:30-17:30 【工作地區】 湖口光復廠：新竹縣湖口鄉光復路12號 ◎依學經歷、科系、經驗相關性、特殊需求證照及專長等條件核敘個人薪資。

1. 規劃生產設備操作流程，降低製造成本，使人員正確使用機器及降低故障率 2. 評估新設備之整體效能，並將其導入產線 3. 定期做生產設備之維護，使機器運作順利 4. 調整機台&提高機台生產率及降低生產成本 5. 生產設備除錯，製程問題進行分析，檢視錯誤原因，如: 負擔過重、溫度過高等並找尋解決辦法 6. 提高並改善工作場所安全 7. 作業指導書的編寫及安排 8. 打版.樣品.估價並管理樣品交期事務 9. 可配合常態性加班佳

我們是專注於人造纖維製造的領先企業，致力於提供高品質人造纖維產品，服務範圍涵蓋不同產業所需的高性能材料。我們堅持技術創新與品質優化，為客戶提供最佳化的生產和服務體驗。 本職務為技術職，透過分階段的學習和培訓，協助助理工程師快速成長，並提供清晰的升遷機會。以下為相關工作內容： 工作內容： 1. 參與人造纖維產線的日常運作，具體包括生產流程監控、設備操作、產品品質檢測及異常報告。 2. 協助完成生產線之日常維護作業，確保機器設備正常運作。 3. 學習與掌握物性的基本概念，並支援週邊設備的更換與操作。 4. 培養應對及解決生產線異常狀況的能力，熟悉相關處理流程與作業。 5. 協助執行新產品開發試產過程，進行技術數據記錄與改進建議。 6. 分析並參與生產規格調整與優化討論，提出改善策略。 7. 定期檢視並更新操作手冊或技術指引，提升團隊作業效率及穩定性。 8. 支援跨部門溝通需求，確保生產與品質要求無縫對接。 ※ 本職位需配合夜間出勤（需待命），將提供相對應之加班費及交通津貼，完整保障您的權益。 我們傳承深耕多年的導師制度，幫助您快速融入團隊並穩定成長。如果您對提升生產技術水平及累積紮實經驗感興趣，我們誠摯邀請您加入我們的大家庭！ 立即投遞履歷，期待與您攜手共創佳績！

1. 連接器開發前的結構模擬分析與提供改善方式 2. 連接器的散熱模擬分析與提供改善方式 3. 開模後的檢討與改善對策

＜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)