BMC 韌體工程師

＜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.

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. 參與系統開發專案規劃討論與技術分析，並可獨立完成網頁開發及維護。 

2. 與開發園隊協作，依照文件串接 RESTful API, 並能有效處理資料。 

3. 規劃易維護、可擴展的元件及模組，提升開發效率。 

4. 關注 Web 技術發展，學習並試導入新技術。 

5. 具備前端實務開發經驗至少2年。 

6. 獨立解決問題的能力，且熟悉各瀏覽器及裝置的開發偵錯工具。 

7. 負責任與積極的態度，對工作及所產出的程式進行品質管理，並随時考慮優化可能。

【工作職責】 

•負責 SAP ABAP 程式與 SAP Fiori 應用系統之設計、開發與維護。 

•與功能顧問及技術團隊密切合作，蒐集並分析業務需求，提供專業技術解決方案。 

•執行系統分析、程式除錯與問題排查，確保系統穩定運作並有效解決技術問題。 

•持續關注並學習 SAP ABAP / Fiori 相關之最新技術、工具與最佳實務。 

【Responsibilities】 

•Design, develop, and maintain SAP ABAP programs and SAP Fiori applications. 

•Collaborate with functional consultants and technical teams to gather business requirements and deliver effective technical solutions. 

•Perform system analysis, debugging, and troubleshooting to identify root causes and resolve technical issues. 

•Stay up to date with the latest SAP technologies, tools, and best practices related to ABAP and Fiori development.

1.AIOT系統管理開發,應用於智慧工廠(智能安防與流程監控) 

2.負責管理平台之 UI/UX 設計開發 

3.串接後端 API，實現數據即時同步與高互動的使用介面 

4.開發儀表板，將數據與分析結果以圖表直觀呈現，輔助決策 

5.優化大量數據呈現時的瀏覽器效能，設計多維度的數據篩選與查詢機制

【工作內容】 

1. 系統規劃與流程改造 

2. 系統設計及程式撰寫 

3. 主流雲平台使用與環境配置管理 

4. 用戶教育訓練及問題排除 

【工作地點】 

台北土城、高雄軟體園區 (若您希望派駐國外也可以) 

未來公司採全球化配置, 將會有許多短期出差的機會

• 規劃AI服務架構，協助客戶導入。 

• AI相關數據架構、建模、應用分析規劃。 

• AI相關產品、技術學習研究。

【工作內容】 

MES 製造執行系統-Manufacturing Execution System 

1.負責對部門內部專案進行支持、監控和管理，協助部門主管實現專案目標； 

2.支撐MES體系執行和改進，關注專案過程執行，識別、推進部門內部過程改善； 

3.對部門專案進行管理、監控、審計和彙報，幫助專案經理協調、解決專案問題，保證專案順利完成； 

4.支援體系流程，支援工具使用，參與流程和工具改進； 

5.組織部門級項目立案/結案/外包合同/變更評審…等工作； 

6.對專案資料進行匯總和管理，定期上報，為領導決策提供資料支援； 

7.支撐專案KPI績效考核； 

8.建立部門內部知識共用平臺，促進部門專案管理能力提升； 

9.培育專案管理幹部，避免組織人員異動影響專案時程或組織； 

10.支援海外相關專案導入 

11.完成主管交辦事項

1. 主機板測試程式開發(伺服器，儲存器) 

2. Linux測試平台及模組維護 

3.Windows測試平台及模組維護 

4.自動化測試軟體開發 

5.系統壓力測試軟體開發

1. 系統平台上的使用者介面視覺設計  

2. 以使用者中心設計為原則，設計直覺又優美的使用者介面  

3. 使用者介面上的共用元件視覺設計及相關使用文件產出  

4. 軟體介面上所需的圖像及動態設計  

5. 使用者介面設計的易用性評估與改善

您將共同進行以下工作項目: 

1. HPC軟硬體集群架構規劃 

2. 網路系統設定與管理 

3. HPC 叢集建置與管理自動化

* 雲平台產品的售前與售後支持 

* 提供維運團隊技術支援 

* 對用戶需求做分析及提供解決作法 

* 對團隊內部及合作單位進行教育訓練

配合高速成長的AI伺服器業務，我們正在擴大招募HPC (高效能運算) 集群設計、效能測試與分析的團隊。我們期待您有分析並系統性解決問題的能力，願意在世界級的先進平台上開發精進，和公司以及客戶共贏共榮。您將共同進行以下工作項目: 

1. 測試自動化與數據分析 

2. 機器學習效能分析 

3. LLM 訓練效能分析 

4. 分散式系統軟硬體調校

1. 規劃伺服器產品自動化測試方案 

2. 開發伺服器產品自動化測試程式 

3. 負責導入實驗室或工廠自動化測試 

4. 開發客戶或實驗室需求的軟體工具 

5. 協助開發研發單位自動化測試需求

1. 使用Lua和Objective-C在Mac OS上開發軟體用於自動化硬體功能測試。 

2. 與跨職能團隊合作，分析、排除並解決硬體功能測試問題。 

3. 使用Python或其他語言開發用於工程流程改進的軟體。 

4. 前往海外支援新產品工程需求開發。

ATA 產品開發 

1. 負責通訊產品嵌入式系體軟軔體開發 

2. 負責產品後續維護、問題分析及除錯

協助開發跨平台應用程式 (APP/Web) 與後端 API 服務；參與軟體專案的需求訪談、功能開發與規格文件彙整。配合執行 CI/CD 自動化整合測試與程式碼審閱，支援應用 AI 模型進行任務自動化之專案實踐，並學習撰寫高品質的技術佈署文件 (TDD)。 

Assist in developing cross-platform apps and backend APIs. Participate in requirement gathering and technical specification compilation. Support CI/CD automated testing and code reviews. Collaborate on projects utilizing AI models for task automation and learn to author high-quality Technical Deployment Documents (TDD).

協助全球 AI 算力平台架構的環境佈署與配置作業；參與雲端服務資源的日常維運、自動化資源分配之參數設定及性能監控。配合利用容器化技術 (Docker/K8s) 進行效能瓶頸初步排查，支援優化 MLOps 工作流並協助撰寫技術維護文件。 

Assist in environmental deployment and configuration of global AI computing platforms. Participate in daily operations of cloud resources and parameter setting for automated resource allocation. Support initial performance troubleshooting using container technologies (Docker/K8s) and help optimize MLOps workflows and documentation.

1.AIOT系統管理開發，應用於智慧工廠(智能安防與流程監控) 

2.負責後端架構設計，資料庫效能優化及系統運維 

3.建立高效可靠的串流通道，處理IOT設備大量數據存取 

4.與前端協作，產出可用於輔助決策的指標API 

5.確保系統擴展性，支援未來的數據挖掘與 AI 模型整合

To design, develop, and integrate diagnostic software solutions for servers, storage, and AI accelerator platforms, enabling automated testing and efficient issue resolution in collaboration with hardware and firmware teams. 

· Design and implement diagnostic software for hardware platforms. 

· Develop automation tools and scripts for testing and validation. 

· Integrate diagnostics with production and lab environments. 

· Troubleshoot hardware and software issues with cross-functional teams. 

· Document diagnostic procedures, tools, and technical guides. 

· Evaluate and adopt new tools or technologies to enhance diagnostics. 

Required Skills / Tools / Experience 

· Proficiency in Shell Script, Python, C/C++ 

· Strong Linux environment usage (Ubuntu preferred) 

· Knowledge of system programming, networking, algorithms, and data structures