ADAS演算法工程師

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.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.數據治理實施，包括資料模型、資料定義、元數據、資料品質等 

2.建構數據工作流(Data Pipeline)、導入數據工程自動化和敏捷實踐(DataOps) 

3.熟悉數據架構規劃、數據源開發、數據蒐集與處理、數據探勘與加值 

4.數據建模 : 依主題挑選適當模型方法與參數處理進行多類型建模與冠軍模型挑選，與商業分析師合作進行統計分析模型及最佳化的研究與開發。 

5.視覺化應用 : 善用視覺化工具(PowerBI)溝通特徵值與模型分析結果。 

6.具備跨單位的大型專案管理實務 

7.具備良善的溝通技巧及專案團隊協作能力

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. 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

＜About the job＞  

As the Senior Data Engineer or Data Architect, 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＞ 

*Type 1：Senior Data Engineer 

Responsible for acquiring data using API, Web scraping, or other data accessing protocol/scripting and developing the ETL data pipelines, and the data aggregation systems. Using software development experience to design and build high-performance automated systems. As below: 

1. Data Processing 

(1)Data ETL(Extracting/Transforming/Loading) process engineering and querying from relational data management(such as SQL Script). 

(2)Building systematic data quality processes and checks to ensure data quality and accuracy. 

(3)Solid coding experience in Python or Java. 

2. Data Pipeline Development 

(1)Develops a data integration process, including creating scalable data pipelines and building out data services/data APIs. 

(2)Create a data processing automation and monitoring mechanism by optimizing the data pipeline process.  

(3)Experience with dataflow/workflow/management tools, such as Apache Nifi, Apache Airflow, Azkaban, etc., is preferred. 

3. Data Crawling 

(1)Build scalable tools that automate web crawling, scraping, and data aggregation from various web pages using frameworks such as Scrapy. 

(2)Accessing data from REST APIs, particularly in parsing data in disparate formats such as JSON and XML, and developing automated engineering.  

(3) (Nice to Have) Knowledge of server-based front-end/UI technologies, including Vue/React and HTML/CSS, is preferred. 

*Type 2：Data Architect 

Responsible for designing, implementing, and maintaining scalable and reusable system architectures/data architectures for complex data structures and large data in data science and AI projects. As below: 

1. Data Schema Design 

(1)Collaborate with the team to design DB/Table Schema and Data Schema. 

(2)Consolidate the requirements and use data engineering tech to design and implement a robust Data Mart.  

(3)Experience handling all kinds of structured/semi-structured/unstructured data and streaming data is preferred. 

(4)Hands-on experience with Dimensional Data Modeling(Column-based data warehouse) or NoSQL Schema design. 

2. Data Platform Architecture 

(1)Design and build data infrastructure/platform components to support complex data pipelines ingesting various data from multiple internal and external data sources and processing. 

(2)Familiar with Big Data frameworks and processing technologies, ex: Hadoop, Apache Spark, NoSQL ...etc. 

(3)Familiar with AZURE or AWS cloud data services(hands-on experience with cloud infrastructure will be a plus) 

(4)Familiarity with the Linux OS environment, the Shell Scripting, and infrastructure knowledge.  

(5)(Nice to Have)Experience with declarative infrastructure/container technologies, such as Docker and Kubernetes (k8s/k3s). (Nice to Have).

1. 通訊設備嵌入式系統研發 

2. IP network通訊協定研發 

3. 物聯平臺研發(LPWAN GW, module/sensor, IoT platform) 

4. 數據平臺開發(數據分析,演算法規劃,解決方案規劃/數據處理,資料串接/視覺化)

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. 建構 x86 / ARM 平台之 Linux RTOS 執行環境 

2. 設計與整合 EtherCAT / Modbus 等通訊協定與驅動模組 

3. 串接伺服器、感測器、相機等設備通訊控制 

4. 負責控制模組與 AI 模型的整合部署與環境建置

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. 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. 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.

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.

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

＜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.

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.

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

We are seeking a highly motivated Software Team Leader, who combines technical leadership, system-level thinking, and cross-functional collaboration with R&D, Operations, and global customers to enable efficient diagnostics, automation, and intelligent data integration. 

Responsibilities 

•Lead the software team to design, develop, and integrate diagnostic software solutions for AI server and storage platforms. 

•Build a unified Diagnostics OS that supports modular and reusable test components across multiple products and customers. 

•Drive automation, standardization, and integration with production lines. 

•Collaborate with R&D and Operations to enable efficient issue diagnosis and resolution throughout the product lifecycle. 

•Develop and maintain automation tools, test scripts, and diagnostic libraries for manufacturing. 

•Define and enforce standard interfaces and log formats for seamless integration with the operation flow. 

•Document diagnostic procedures, APIs, and best practices. 

•Evaluate and adopt new tools or technologies to enhance testing efficiency and data analytics. 

Qualifications 

• Strong communication and problem-solving skills, able to respond quickly to customer and factory issues from different time zones. 

• Solid understanding of server system, AI server architecture, and diagnostics workflows. 

• Experience leading software teams and coordinating with cross-functional teams for global customers. 

• Proficient in software development lifecycle management and quality assurance practices.

1.AI / Compute / Storage伺服器測試軟體開發及相關軟體模組維護(含 板階、系統階、櫃階 測試 

2.Compute / Storage伺服器壓力測試軟體開發及維護:主要為系統階測試 

3.依伺服器組件、功能、出貨規格 建立 測試計劃，完成測試軟體套件開發後導入工廠端交付測試執行團隊: 

依專案 需短期出差美國、墨西哥 (1個月/次，年累積三個月以下)