求職服務專線
台北 02-2912-6104 轉 2
   02-7703-3104 轉 2
意見回饋
廠商求才專線
台北 02-2912-6104
   02-7703-3104
台中 04-3700-6104
上海 86-21-50277104 轉 1
意見回饋

Software Engineer – Machine Learning

  • 全職

*Prototype, develop, test and optimize ML models.
*Apply ML and other statistical approaches to generate insights on structured and unstructured data.
*Collect new data and statistics from multiple sources and generate statistical analysis.
*Mentor and support the training of technical and non-technical teams in data science and machine learning.

工作條件

  • 工作經歷: 二年以上
  • 學歷要求: 大學 碩士
  • 語文條件: 不拘
  • 其它條件: Minimum qualifications:
    *BS degree in Electrical Engineering, Physics, Mechanical Engineering, Computer Science, or equivalent practical experience.
    *Understanding in ML, including knowledge of the mathematical underpinnings behind various methods (e.g. regression techniques, neural networks, decision trees, clustering, pattern recognition, dimensionality reduction)
    *Experienced with signal processing algorithm development.
    *Experience with scripting languages (e.g Python/MATLAB) and software development languages (e.g C/C++).
    *2 years of relevant work experience.

    Preferred qualifications:
    *Master’s degree, further education or experience in Electrical Engineering, Physics, Mechanical Engineering, Computer Science or other technical related field.
    *Ability to use a wide variety of open source technologies.
    *Task oriented with ability to set goals and complete deliverables.
    *2 years professional experience developing and implementing machine learning models
    *Basic understanding of managing and using AWS, GCP or other cloud related services.

福利制度

法定項目

其他福利

1.提供具競爭力的優渥薪酬
2.依營運狀況與個人績效,發行員工認股權憑證
3.發放績效獎金、三節獎金及推薦人才獎金
4.提供完善之團體保險與年度健康檢查
5.定期舉辦員工聚餐,增進主管與同仁彼此瞭解及互動
6.依職務別提供員工職能教育訓練
7.社團活動補助
8.彈性上下班制度
9.優於勞基法之休假制度,如旅遊假等

更新日期:2022-01-18

應徵方式

  • 職務聯絡人: 林小姐
  • 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0-5人應徵
經歷分佈
新鮮人0%
1~3年50%
3~5年0%
5~10年50%
10年以上0%
學歷分佈
碩士及以上50%
大學50%
專科0%
高中0%
高中以下0%
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