RD-系統整合測試工程師(土城)-E事業群

＜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.客戶對接及專案執行  

2.海外廠區出差協助  

3.ISO27001認證導入及體系運維  

4.風險評估及改善  

5.IPGuard, Nessus Pro, 防毒管理運維/監控/異常處理/升級/優化等理

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

參與集團全球營運系統的模組維護與功能優化；協助伺服器建置、日常網路維運與資安監控作業。配合集團數位轉型計畫導入相關 IT 工具，支援資安防護政策的落實，並協助整理潛在系統風險的改善報告，學習大型企業資訊治理流程。 

Participate in module maintenance and optimization of group systems. Assist in server setup, network operations, and cybersecurity monitoring. Support the implementation of IT tools for digital transformation and assist in the execution of security policies and risk reporting.

1. 數據中心IT架構規劃 

2. 冷凍空調、電源配置規劃 

3. 確認終端客戶IT需求