機器學習工程師 AI/ML Engineer(Data Science & AI Team)
面議（經常性薪資達4萬元或以上） 40000元
新北市土城區
3~4年工作經驗
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
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