清大專區

1. 研究光電元件、光電物理及技術、積體光學系統特性及理論。 2. 設計固態光電元件 3. 針對光電材料、元件產品之製作、管理及設備採購作業，提供技術性建議及相關諮詢。 4. 瞭解雷射特性及其應用規格，分析雷射晶片後工程序的封裝測試及失效模式。 5. 設計、開發電子電路系統。 6.進行PCB板電路設計及分析

★工作地安排：工作地於高雄大寮，視專案及產品會有國內外出差需求★ 歡迎有志者一同加入！ 1.負責處理售後問題，客訴分析處理及彙整回復 2.產品品質異常分析及8D報告撰寫 3.負責客戶端產品及品質問題的回覆 負責產品:Cell or Pack

★工作地於苗票頭份，視產品或專案會有出差之需求，歡迎有志者一同加入！ 1.負責現場審核、過程審核、產品審核 2.各廠區間的交互審核，及改善效果確認 3.培養稽核員，建立有效的內部稽核團隊

1. BB circuit design (4G/5G) 2. BB parts function testing and performance tunning. 3. BB parts layout review 4. Discuss test process with MFG and customer. 5. Prepare product BOM list

產品：Gateway/STB/OTT 1. 產品解決方案可行性研究 2. 產品硬體規格制訂與報價 3. 產品硬體線路設計與測試 4. 產品法規認證與生產支援 5. 專案計畫會議討論 6. 產品2nd source導入

產品：Gateway/STB/OTT 1. 產品解決方案可行性研究 2. 產品硬體規格制訂與報價 3. 產品硬體線路設計與測試 4. 產品法規認證與生產支援 5. 專案計畫會議討論 6. 產品2nd source導入

1.負責產品硬體可靠度驗證並對產品問題追蹤、分析及改善 2.按照時程完成專案所需驗證 3.訂定測試計劃並撰寫測試報告 4.相關國際法規的研讀與了解 5.與客戶討論並確定相關測試要求 6.開發與產品有關之可靠度驗證技術

1.新產品客制芯片失效分析 2.新產品硬件電路及系統設計失效分析 3.新產品維修手冊撰寫及產線工程師培訓 4.協助量產維修良率提升

1. Smartphone新產品導入階段硬體研發和測試驗證 2. OLED顯示器光學設計及電路驗證和試產 3. Touch sensor電路設計、驗證和試產 4. 負責Display/Touch失效分析與技術驗證 5. 具備英文溝通能力以與客戶技術研討 6. 配合出差海外協助客戶設計開發與測試驗證

★工作地於苗票頭份，視專案/產品會有國內外出差之需求★ 歡迎有志者一同加入！ 1.推行6 SIGMA、與QCC活動 2.負責品質工具培訓 3.改善提案、及提案改善 4.產品可靠度分析

1. Product EMC Design and Verification test. 2. Product EMC Issue Analysis and Debug. 3. Product EMC World-wide Certification.

1. 全球交易模式與損益管理. 2. 各項營運KPI與成本管控: 營收/應收帳款/存貨/費用 3. 須配合出差美國/墨西哥. 4. 其他主管交辦專案

1. 系統架構可行性評估。 2. 電路設計。 3. 偵錯除錯。 4. 與各function team合作完成測試。

負責產品：IP cam、Dash cam 1. 影像品質調整 2. 影像品質測試驗證 3. 產線測試結果分析與確認 4. 開發相機產品相關測試項目

1. BOM製作 2. 尋找component 2nd source 3. 與工廠協調物料問題

1.與客戶討論擬定測試項目 2.Server 可靠度測試及分析 3.專案前期:RFQ/polling/NRE/測試規劃評估 4.專案中期:Test Plan/Test Report/專案執行 5.專案後期:問題追蹤及分析驗證

Job Summary: The Statistician/Data Scientist will be responsible for all advanced statistical methods utilized for improving product quality, production yield, and factory effectiveness as well as finding the root-causes, along with other consulting services such as customer targeting and lead scoring in support of sales and marketing activities worldwide. Key Responsibilities: • Design, implement, and refine advanced statistical/Machine Learning models to support product quality improvement, increasing yield and factory effectiveness. • Cultivate strong relationships with production line engineers, IT, and other key stakeholders to ensure alignment of modeling initiatives with company objectives and to identify new hypotheses for model improvements. • Scale out modeling capacity by driving infrastructure improvements such as automation of data preparations, model training, implementation, and optimization. • Support integration of models into tools for use by product engineers and business analysts. • Engage with customers to develop and customized data analytics solutions to address special needs. • Address ad hoc queries from management and present actionable recommendations in a clear, concise, and convincing manner. • Communicate the application and benefits of using various predictive modeling techniques to improve decision-making to customers and stakeholders. • Collaborate effectively with team members, whether leading projects or supporting initiatives led by others. • Provide direction, training, and guidance to less experienced team members.

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.