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台北 02-2912-6104 轉 2
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台北 02-2912-6104
   02-7703-3104
台中 04-3700-6104
上海 86-21-50277104 轉 1
意見回饋

機器學習工程師 AI/ML Engineer(Data Science & AI Team)

  • 全職

工作內容:

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).



.Type1: AI/ML Engineer (Deeping Learning/Machine Learning Engineer)
(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.

.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, evaluating, and delivering/deploying NLP models.


.Type1: AI/ML Engineer(Deeping Learning/Machine Learning Engineer)
(1) Experience with any one of Machine Learning, Statistical Modeling, Deep Learning(Nature Language/Image) model/algorithm building of the practical application in the industry.
(2) Familiarity with programming languages like Python, R, or Java. (Good programming skills in Python is a plus)
(3) Familiar with Python Libraries, e.g., Numpy、Pandas、Scikit-Learn、SciPy、Matplotlib, etc.
(4) Knowledge of Big Data with Machine Learning/Statistical modeling related technologies such as Spark MLlib or PySpark or SparkR/SparklyR.
(5) 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 in manipulating and integrating the unstructured, semi-structured, and structured data.
(5) Excellent knowledge and demonstrable experience using open-source NLP packages such as NLTK, Word2Vec, Standford CoreNLP, SpaCy, Gensim.

工作條件

  • 工作經歷: 三年以上
  • 學歷要求: 碩士以上
  • 語文條件: 英文 -- 聽 /中等、說 /中等、讀 /中等、寫 /中等
  • 其它條件: **Nice to have (not required)
    .Type1: AI/ML Engineer
    (1) Experience in MLOps lifecycle management (build, deploy, and production support)
    (2) Knowledge of ML pipelines skills, including model serving and model performance monitoring and feedback components
    (3) Experience in Cloud Computing and Distributed Solutions

    .Type 2: NLP AI Engineer
    (1) Familiar with Deep Learning frameworks like TensorFlow, PyTorch, Keras
    (2) Knowledge of state-of-the-art DL/ML algorithms such as BERT, ELMo, GPT, GPT-2, XLNET, LSTM-CRF, etc.
    (3) Experience in NER(named entity recognition)、Entity Linking、SQuAD、Chinese word segmentation.

福利制度

年薪及獎金:
發放2個月年終獎金,表現優異者視年度營運及個人表現發放績效獎金與紅利。
福利:
1.贈送員工生日禮品(禮金) 、節慶禮品等。
2.年終活動與摸彩。
3.補助員工文康娛樂活動(如:建置員工健身房、設置盲胞按摩服務等)。
4.健康促進活動(如:專題演講、減重活動等)。
5.健康及醫療諮詢。
6.獎勵員工生育(含員工配偶),並針對懷孕女性員工提供交通補助、孕婦禮遇等照護措施。
7.員工結婚禮金及喪葬慰問金。
8.員工團保。

更新日期:2021-12-22

應徵方式

  • 職務聯絡人: 劉'S
  • 聯絡E-Mail: (請利用104履歷表應徵此工作) 我要應徵
  • 洽: 不接受電洽
  • 洽: 不接受親洽

應徵分析

兩週內6-10人應徵
經歷分佈
新鮮人25%
1~3年13%
3~5年38%
5~10年25%
10年以上0%
學歷分佈
碩士及以上100%
大學0%
專科0%
高中0%
高中以下0%
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