數據科學家Data Scientist (Data Science & AI Team)

* 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。

＜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. 熟悉微服務平台建置、維護與管理 (Kubernetes(K8S)、Docker)  

2. 經營/維護/優化 DevOps 工具 

3. Jenkins等 持續整合/建置環境建置與維護(CI/CD)  

4. Google Test 經驗 

5. 測試報告追蹤 

6. 可自主建立已上流程系統(必要).

＜About the job＞  

As the AI Software Engineer, 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＞ 

Responsible for deploying the AI/Data Science collaborative framework and building the AI model and data operating infrastructure. Using software development experience to design and develop high-performance automated systems for AI development and operation. As below: 

．Collaborating with Data Scientist/AI ML Engineer team, other software system development teams, and the infrastructure team. 

．Ability to utilize various tools/methods to build the MLOps/DataOps/DevOps and deploy and manage the AI Development framework and infrastructure 

．Developing infrastructures for data transformation and ingestion and automating important infrastructure to process data 

．Deploy AI models to the Inference server and optimize the performance of the model serving operation reliably and efficiently. 

．Assist the Data Scientist/AI ML Engineer team in converting the AI models into APIs to serve other systems or integrate with other systems. 

＜Skill Sets＞ 

(1)Excellent problem-solving and troubleshooting skills. 

(2)Genuine passion for learning new technologies and open-source projects. 

(3)Familiarity with Python and Java (python is a must) 

(4)Good understanding of the Linux OS environment, the Shell Scripting, and infrastructure/networking knowledge.  

(5)Experience with GitLab CI/CD 

(Nice to have but not necessary)  

(1)Experience with MLops and Model Serving tools. 

(2)Experience in GPU programming and performance tuning 

(3)Being familiar with AZURE (or AWS) cloud infrastructure will be a plus 

(4)Familiar with declarative infrastructure/container technologies, such as Docker and Kubernetes (k8s/k3s)

1. 根據客戶應用需求,提供雲端產品技術整合之系統架構,提供符合客戶需求之產品服務 

2. 跨部門協調研發及生產單位,提供系統整合產品服務 

3. 研究及分析雲服務市場需求並設計符合客戶需求之產品

1. 規劃伺服器及Rack Level產品自動化測試方案 

2. 規劃及開發 Rack Level 自動化測試程式 

3. 規劃及導入實驗室或工廠自動化測試 

4. 規劃及開發客戶或實驗室需求的軟體工具 

5. 協助研發單位規劃自動化測試需求

1. CI/Automation/Test Automation (Python) 

2. Web Application (Python, Node.js, Java) 

3. 網管系統或 BMC/Redfish related external system (Python, Linux shell) 

4. AI, BigData, Datastore development (Python, Java)

1. 雲服務之網路架構規劃、設計 

2. SDN、NFV之規劃、導入 

3. 識別及解決網路問題 

4. 網路設備管理、維護 

5. 客戶應用上雲之網路架構諮詢、規劃

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

負責Android行動應用程式的設計開發、介面整合與日常維護，以提升行動端使用者體驗與業務營運效率。  

1.負責Android用戶端產品架構設計、代碼開發及維護工作。  

1.能夠獨立完成高品質的功能模組開發，確保代碼性能、穩定性和相容性。  

2.參與App的性能優化（啟動速度、記憶體、包體積）、體驗優化及疑難問題攻堅。  

3.跟進Android前沿技術，進行技術預研和難點攻關，將新技術引入到現有產品中。  

4.配合產品、測試、運營團隊，反覆運算需求，保證專案按時高品質交付。  

5.編寫和維護相關技術文檔，參與代碼Review，提升團隊整體技術水準。

負責電腦視覺演算法、AI模型部署與影像應用系統的開發設計、功能整合與效能優化，以優化智慧化影像分析與自動化營運效率。

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

• 規劃和執行 DevOps、CI/CD的長期策略。 

• 帶領和培養 DevOps 團隊成員，提供技術指導並進行績效評估。 

• 促進開發與營運團隊之間的協作、溝通與知識共享，強化 SRE思維。 

• 負責設計、部屬和維護自動化的 CI/CD 及品質管理 (如 Jenkins, GitLab CI, Sonarqube, 及相關監測工具等)。 

• 根據專案需求，建立、管理和維護多套應用系統環境。 

• 熟悉相關配置管理工具，確保不同環境的配置一致性。 

• 部署和管理集中式監控 (如 Prometheus, Grafana) 和日誌系統 (如 ELK Stack, Splunk)，以主動式警報和故障排除流程。

1. 架構設計與搭建：結合 HIS、EMR、PACS 等醫療系統需求，設計智慧醫院及機器人平台高可用資料庫架構；選型關係型 / 非關係型資料庫，搭建優化集群。 

2. 數據集成與支持：參與數據中臺建設，完成 ETL 數據整合；支持開發團隊設計評審，為科室提供技術諮詢與培訓。 

3. 安全與合規：管控數據訪問許可權，加密敏感醫療數據；配合審計與監管檢查，落實合規整改。 

4. 日常運維與監控：負責資料庫實例、許可權、性能調優；搭建監控體系（CPU、IO 等指標）；制定並執行備份恢復策略。 

5. 技術迭代與應急：評估新技術（雲資料庫、分佈式等），制定升級遷移方案；制定應急預案，處置宕機、數據損壞等突發問題。

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)