【DQE】I-AI人工智能算法工程師/主管

＜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/Algorithm Models 

•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. 

•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. 

•Able to use the cutting-edge technologies to solve the practical problems 

＜Skills＞ 

•Experience with any one of Machine Learning, Statistical Modeling, Deep Learning, 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. 

•Experience in setting up supervised & unsupervised learning models including data cleaning, data analytics, feature creation, model selection, performance metrics & visualization

BMC(Baseboard Management Controller基板管理控制器). Firmware supported on worldwide tier one customer projects of Clouding & Enterprise server. 

1. 伺服器BMC韌體設計開發 

2. 既有專案維護 

3. 跨單位技術上的溝通探討 

4. 了解客戶需求與熟悉產品規格

CESBG-產品線Server 

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

BMC(Baseboard Management Controller基板管理控制器). Firmware supported on worldwide tier one customer projects of Clouding & Enterprise server. 

1. Embedded Linux development on ARM/MIPS SOCs.  

2. Linux technology and GNU tool chains. 

3. Device drivers or kernel modules development.  

4. Scripting like, shell script, Python, Perl. Web technologies of JavaScript, html, CSS and AJAX development.

1. Manage team 

2. BIOS development planning and management 

3. Across function teams communication 

4. Customer relationship maintain 

5. Cultivate talents

1. 制定自動化設備視覺應用改進完善方案 

2. 視覺應用工作整體把控 

3. 機器視覺方案設計及可行性分析 

4. 自動化機器視覺算法設計及開發 

5. 與客戶檢討設備方案及驗證狀況改善推動 

6. 有良好的帶隊能力或專案驅動力

1. Server Liquid Cooling System Control Firmware Development 

2. Server Liquid Cooling System Control Circuit Design 

3. Server Liquid Cooling System Control System Analysis

1. 伺服器BMC韌體設計開發 

2. 協調客戶需求與產品規格 

3. 既有專案維護 

4. 跨單位技術溝通探討

1. 伺服器BMC韌體設計開發 

2. 既有專案維護 

3. 跨單位技術上的溝通探討 

4. 了解客戶需求與熟悉產品規格

1.數位邏輯設計並熟悉RTL Coding架構。 

2.熟悉 Xilinx、Altera FPGA 架構與設計。 

3.研發設計網通應用IP。 

4.協助開發與驗證FPGA電路(Schematic)。

1.解析伺服器硬體架構與線路設計，掌握系統運作原理。 

2.研究並實作 BMC 與各式硬體介面的通訊協定。 

3.在 Linux 環境中進行開發與除錯，熟悉 Git、伺服器建置及開發工具操作。 

4.使用 OpenBMC 平台進行功能開發、系統整合與驗證，持續優化系統穩定性與可維護性。 

5.與跨部門團隊合作，協調軟硬體整合進度，並協助工廠進行問題分析與除錯，確保產品品質與量產穩定性。

1. Embedded Linux development on ARM/MIPS SOCs.  

2. Linux technology and GNU tool chains. 

3. Experience of developing device drivers or kernel modules.  

4. Cloud Server, Storage Server, Data Center Server & Micro Server firmware development.

嵌入式系統軟韌體開發/產測程式開發BMC 韌體開發

1. Lead the lead of firmware team for server project.  

2. Study technical issue for project‘s needs. 

3. Review & sign off requirement specification. 

4. Review engineer design. 

5. Review function/interface specification. 

6. Review bug fixing. 

7. Help the design and review the common definitions for debugging and profiling.

您將共同進行以下工作項目:  

1. DPU 韌體開發  

2. NVMe over RDMA系統分析與設計  

3. 分散式網路儲存系統效能優化  

4.開源軟體開發與測試  

5. Redfish API開發維護

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. 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.車用ADAS 攝影鏡頭、光達、雷達相關應用 

2.建立感知融合策略經驗(Camera Radar/Camera 

3.點雲物件辨識模型建立 

4.串接自動駕駛模擬器與系統驗證開放式平台之軟硬整合 

5.配合開發流程撰寫相關文件 

6.熟悉以下語言/ 一項或多項))：C++/Python/TensorFlow/PyTorch 程式開發能力，具ROS2 相關開發經驗尤佳 

7.主管交辦事項

＜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