交大專區

Job Summary 此職位為偏軟體與資料工程導向的工程師角色，主要負責將實際使用者 (User) 需求轉化為可落地的資料流程、後端服務與視覺化應用。 工作重心聚焦於資料處理、系統整合、效能與穩定性，並透過與使用單位的密切溝通，持續優化系統與報表，確保資料能被正確且有效地應用於實際業務場景。 Key Responsibilities - 與內部使用者（如工廠、營運或相關單位）溝通需求，釐清實際使用情境，並將需求轉化為具體的系統設計、資料流程或報表規格 - 使用 SQL、Python 進行資料處理、清洗與轉換，設計與維護穩定的資料管線（ETL / Pipeline） - 開發與維護後端服務或 API，支援資料存取、系統整合與應用功能 - 規劃並開發 BI / Dashboard 視覺化報表（如 Tableau），確保資料正確性、可讀性與實際可用性 - 與其他工程師、IT 或跨部門團隊合作，進行系統串接、資料整合與流程優化 - 針對資料量成長或使用情境變化，進行效能調整、架構優化與問題排查 - 持續關注資料品質與系統穩定性，主動發現並改善影響使用者體驗的問題 ※ 本職位重視將資料與系統「做穩、做對、做給人用」，而非以模型或演算法為主要解決手段。

工作內容： ＜About the job＞： We‘re seeking AI/ML enthusiasts with experience and skills in working and are passionate about extending AI/ML expertise. The Data Science & AI team of headquarter IT is developing the frontier and practical analytic technologies that enhance the data value. As the AI/ML engineer, you‘ll join the AI/Big Data Analytics program/projects of headquarter IT and assist in building the model/algorithm to empower data-driven & analytics-driven for driving business value from data insights in this world-class company (Fortune Global 500, 22nd). ＜Job Type Option：＞ *Type1: AI/ML Engineer (Engineering-Oriented) (1) Use Machine Learning/Deeping Learning/Analytical techniques to build models for internal different scenarios and requirements. (2) Building the model lifecycle from data exploration to feature engineering to model evaluation and validity analysis capabilities. (3) Execute efficient, scalable, automated processes for model development, model validation, and model implementation (4) Deploy the model to production and maintain/optimize the models by MLOps. (5) Experience in Azure Data Lake, Azure Databricks, and Azure Data Factory is preferred. (6) Experience in AWS SageMaker is preferred. *Type2: NLP AI Engineer (1) Focused on NLP Algorithm/Machine Learning & Deeping Learning for Text. (2) Develop the Algorithm of NLP(Natural Language Processing)/ Computational Linguistics/Text Mining/Topic Modeling (3) Join the project to build the end-to-end NLP systems, from understanding the requirements to selecting training datasets to model, evaluate, and deliver/deploy NLP models. (4) Fine-tune LLMs and optimize and resolve issues related to LLM usage in production scenarios, enhancing reliability, accuracy, and performance. *Type3: AI/ML Engineer (Analytics-Oriented) (1)Use Machine Learning/Deeping Learning/Analytical techniques to build models for internal different scenarios and requirements. (2)Build the model lifecycle, e.g., from data exploration to feature engineering to model evaluation and validity analysis capabilities. (3)Execute efficient, scalable, automated processes for model development, model validation, and model implementation. (4)Apply quantitative methods including but not limited to above tasks to solve business problems. (5)Being passionate and patient about working with complex data ＜Skills＞ ．Type1 & 3 : AI/ML Engineer(Engineering-Oriented & Analytics-Oriented) (1)Familiarity with any one of Machine Learning, Statistical Modeling, Deep Learning (Nature Language/Image/Time Series) model/algorithm building of the practical application in the industry. (2) Being familiar with Python Libraries, e.g., Numpy, Pandas, Scikit-Learn, SciPy, Matplotlib, etc. (3)(For Engineering-Oriented) Knowledge of Big Data with Machine Learning/Statistical modeling related technologies such as Spark MLlib or PySpark or SparkR/SparklyR. (4)(For Analytics-Oriented) Knowledge of Deep Learning Framework such as TensorFlow/Caffe/Pytorch/Keras. ．Type 2: NLP AI Engineer (1) Experience with text mining algorithms such as word segmentation, POS tagging, named entity recognition...etc. (2) Experience in algorithms and libraries of NLP(Natural Language Processing), especially in machine learning techniques applied to NLP, such as Text mining, Text classification, Information Extraction, Keyword Tagging, and content discovery. (3) Familiar with one general-purpose programming language (e.g., Python, Java, C/C++) (4) Experience manipulating and integrating unstructured, semi-structured, and structured data. (5) Excellent knowledge and demonstrable experience using open-source NLP packages such as NLTK, Word2Vec, Standford CoreNLP, SpaCy, and Gensim. (6) Knowledge of Open source LLMs, such as BERT, BLoom, LLaMA..., etc., and NLP frameworks, like Hugging Face Transformers, PyTorch /JAX

1. 協助新產品開發＆替代料導入 2. 替代料驗証進度追蹤及記錄 3. 零件品質管理 4. 供應商關係管理 (供應鏈狀態/專業技術諮詢) 5. 零件系統與流程優化與管理,包含PCN/ECN/EOL管理 6. 2nd source零件資料庫維護 7. 溝通與協調零件驗證事宜, 報告給 Dell CE team 8. 2nd CM (contract Manufacturer) project (OEM)

＜About the job＞： The Data Science & AI team of headquarter IT is developing the frontier and practical analytic technologies that enhance the data value. As the data scientist, you‘ll join the AI/Big Data Analytics program/projects related to management topics, including Commercial/Industrial Engineering/Supply Chain/Financial Performance/Operation...etc., to build the model or algorithm to empower data-driven & analytics-driven for driving business value from data insights in this world-class company (Fortune Global 500, 22nd). ＜Job Description＞： ．Design, implement and refine advanced Statistical Modeling/Machine Learning/Deep Learning/Numerical Simulation/Optimization Algorithm Models(at least one of the fields) ．Ensure alignment of modeling initiatives with the requirement goal defined by key stakeholders and company objectives and identify new hypotheses for model improvements. ．Executing big data analysis and predictive analytics projects include feature engineering, model building, algorithm development, etc. ．Works closely with a team of data system analysts, business data analysts, data engineers, data platform architects, etc. ．Collaborate effectively with team members, whether leading tasks or supporting initiatives led by others. ．Self-motivated, Result-oriented, and interested in applying quantitative methods to solving business and engineering problems. ＜Skills＞ ．Experience with any one of Machine Learning, Statistical Modeling, Deep Learning(Nature Language/Image), Econometric Modeling, Optimization Algorithm(OR), Numerical Simulation..., etc., model/algorithm building of the practical application in the industry. ．Familiarity with programming languages like Python or R, or Java. (Good programming skills in Python is a plus). ．Advanced ability to perform Exploratory Data Analysis and working knowledge of statistics. ．Ability to visualize data in the most effective way possible for a given task, especially visualize models and results and debug and troubleshoot code and models. ．Big on finding the many insights based on the data and being passionate and patient about working with complex data.

1.硬體電路設計與規劃 2.產品測試與驗證 3.產品規格評估規劃 4.產品量產導入規劃 5.專案解決方案研究

1.設備故障維修及機台性能維護, 保證設備生產效率; 機台測試良率維護與提升。 2.記錄跟進新產品導入中的組裝問題和發現對具體問題的調查、研究和分析. 3跟進解決或上報問題 4.參加新技術測試的實施 5.確保製造過程的優化，保證產出和品質

1.產品製造不良品分析&.DFM分析和改善 2.新產品導入及良率改善&Golden Sample 驗證 3.OBA退貨原因分析及改善 4.領導工程問題的解決 5.產品cost down與品質改善專案

1. 新產品導入測試程式&生產設備治具開發準備 2. 產品Image和function驗證& 試產機台Setup 3. 試產治具耗材設備準備 4. CCD&程序撰寫與驗證 5.試產良率監控,異常故障分析處理及反饋,測試數據的收集.産線操作員的培訓.

1. 伺服器BIOS軟體開發及維護 2. 客戶規格審閱 3. 專案問題分析及解決

1.BIOS development engineering feasility estimation 2.BIOS product specification definition 3.BIOS engineering specification creation 4.BIOS development 5.BIOS debug and mantainance

1.System BOM 2.System Spec 3.System Assembly SOP 4.System Component Approval Sheet 5.System NPI Support (系統階設計、BOM規劃、組裝規劃、Label 規劃、FRU規劃、Cable設計)

Hardware circuit design, layout, pilot run and debug of telecomm / datacomm products. (Router / Switch / Server)

1.Experience in signal integrity simulation of system boards and lab instruments, including VNA and TDR. 2.Experience with PDN characterization and trade off performance & cost. 3.Excellent communication and presentations skills are mandatory

1. PCB疊構與阻抗設計 2. Signal Integrity與Power Integrity 的模擬與分析 3. PCB Layout的Rule制定與審核 4. 訊號量測的審核與除錯 5. TDR/VNA量測

1、根據硬體工程師設計的原理圖，完成PCBLayout工作 2、檢查原理圖和Layout的正確性，生成gerber檔，並跟蹤PCB生產 3、熟悉板廠HDI及SMT製程，獨立完成板廠及SMT廠相關EQ，並協助產品線完成PCB及SMT不良分析及改善 4、加分項：瞭解高速光模塊的EMC SIPI 高速模擬，能從layout方面對高速光模組的EMC SIPI及高速性能提出合理化建議

1.商用車及乘用車結構設計開發驗 2.車輛相關零件之結構強度分析評估且符合機能需求、法規規範 3.整車組裝

〝1.Thermal design and measurement of server, storage and edge server projects 2.Cross functional collaboration and communication 3.Supplier management of thermal parts 4.Advanced thermal solution study〝

1.專案DOE設計與展開、報告與製作 2.DFM規劃與串接上下游製程 3.主導專案規格與樣品產出 4.主導新製程應用與導入 *需配合職務需求出差派駐

1. PCB Layout 2. 板廠工程問題回覆 3. 產線DFx問題解決

1. 新設備/物料/流程/技術評估開發 2. 配合客戶開發新產品 3. 製程問題對策與改善 4. 工程文件撰寫與維護 5. PCB越南建廠相關事宜