CakeResume 找人才

進階搜尋
On
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
Taipei City, Taiwan
Avatar of 吳俊瑩.
Avatar of 吳俊瑩.
曾任
Industrial Engineer @鴻海精密工業股份有限公司
2019 ~ 2023
Data Analyst 數據分析師 / Data Scientist 資料科學家
一個月內
據 ·思緒縝密、規劃能力強,領導團隊朝目標推進 ·積極主動、學習能力佳,持續吸收新知識 [email protected] 技能 Skills • Python • R • Power BI • MySQL • SAP • SAS • Pandas • Numpy • MatplotlibScikit-learn • Seaborn • TOEIC 705 工作經歷 Work Experience 鴻海 Foxconn Industrial Internet, IE工程師/AI專案分析師 , Feb 2019 ~ Jun工業4.0、 數位轉型專案推導 (70%): 協助工
python
R
SAP
待業中
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
國立臺北大學 National Taipei University
經濟學
Avatar of 梁賦康 (Foo-Hong, Leong).
Avatar of 梁賦康 (Foo-Hong, Leong).
Product Manager @東元電機股份有限公司 (TECO Electric & Machinery Co. Ltd.)
2023 ~ 2023
Data Scientist, Data Analyst, Machine Learning Engineer
一個月內
梁賦康 (Foo-Hong, Leong) Taoyuan City, Taiwan Email: [email protected] Tel:Skills • Languages: Python • DataBases: MySQL, SQLite • Infrastructure tools: Github • Machine learning libraries: TensorFlow, Keras, and Scikit-learn • Data visualization tools: Power BI, Seaborn and Matplotlib • Deployment: Streamlit Summary I have been working in Motor Manufacturing Industry for 8 years. My first programming was going to my Bachelor's degree, C++ was the first program I learned. Then I started to learn Python in 2018 at TEDU and my first project was the Stock Trend Prediction by CNN. I kept
Python
Power BI
Data Analytics
就職中
正在積極求職中
全職 / 對遠端工作有興趣
6 到 10 年
國立成功大學 National Cheng Kung University
Mechanical Engineering

最輕量、快速的招募方案,數百家企業的選擇

搜尋履歷,主動聯繫求職者,提升招募效率。

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  • 每日可無限次數開啟陌生對話
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  • 檢視使用者信箱 & 電話
搜尋技巧
1
嘗試搜尋最精準的關鍵字組合
資深 後端 php laravel
如果結果不夠多,再逐一刪除較不重要的關鍵字
2
將須完全符合的字詞放在雙引號中
"社群行銷"
3
在不想搜尋到的字詞前面加上減號,如果想濾掉中文字,需搭配雙引號使用 (-"人資")
UI designer -UX
免費方案僅能搜尋公開履歷。
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職場能力評價定義

專業技能
該領域中具備哪些專業能力(例如熟悉 SEO 操作,且會使用相關工具)。
問題解決能力
能洞察、分析問題,並擬定方案有效解決問題。
變通能力
遇到突發事件能冷靜應對,並隨時調整專案、客戶、技術的相對優先序。
溝通能力
有效傳達個人想法,且願意傾聽他人意見並給予反饋。
時間管理能力
了解工作項目的優先順序,有效運用時間,準時完成工作內容。
團隊合作能力
具有向心力與團隊責任感,願意傾聽他人意見並主動溝通協調。
領導力
專注於團隊發展,有效引領團隊採取行動,達成共同目標。
兩個月內
Senior Software Engineer
Logo of Synopsys.
Synopsys
2022 ~ 現在
台灣新竹
專業背景
目前狀態
就職中
求職階段
專業
軟體工程師
產業
資訊服務
工作年資
1 到 2 年
管理經歷
技能
C
C++
Golang
Kubernetes
Docker
Distributed Systems
Machine Learning
Deep Learning
Tensorflow
Keras
Parallel Computing
CUDA
Compiler
Algorithm
Cloud Computing
語言能力
English
進階
求職偏好
希望獲得的職位
Software Engineer
預期工作模式
全職
期望的工作地點
台灣台北, 台灣新竹
遠端工作意願
對遠端工作有興趣
接案服務
學歷
學校
國立清華大學
主修科系
Computer Science
列印

Experience

Synopsys Inc.

Jan. 2022 - Present

Senior Software Engineer

VCS - Verilog Compile Simulator

C++, C, Compiler Optimization, Parallel Computing, Python

  • Developed and supported debug functionality for SystemVerilog compile simulator
  • Parallelized design traversal in FSDB waveform dumping, speeding up runtime by 3x with multithreading
  • Optimized FSDB gate-data loading and reduced 10-60% runtime memory footprint, benefiting customers running hundreds-of-GB designs with tight memory budgets
  • Initiated a project to migrate STL hash tables to Abseil Swiss tables for a millions-line code base, reducing up to 70% peak memory usage and speeding up hash table queries by 100%
  • Debugged and resolved urgent customer issues in tight timelines (< 1 day TAT) with limited information, tools, and access to the environment

MediaTek Inc.

July 2020 - Aug. 2020

Software Engineer Intern

C, Python, Machine Learning

  • Designed memory management algorithm & firmware for real-time embedded system
  • Introduced machine learning and data visualization to automate issue analysis, saving 90% of human effort

Projects

Voda Scheduler

Feb. 2021 - Nov. 2022

 https://github.com/heyfey/vodascheduler  

(30+ stars)

GPU scheduler for elastic/distributed deep learning workloads in Kubernetes cluster 

Golang, Python, Distributed Systems

  • Architected and built a GPU scheduler using microservices architecture on top of Kubernetes and various open-source projects
  • Sped up overall training time by 2.38x and increased cluster utilization by 1.4x with
    • State-of-the-art scheduling algorithms with resource elasticity
    • Topology-aware scheduling & worker migration to consolidate resources
  • Designed and implemented heterogeneous scheduling, auto-scaling, and fault-tolerant mechanisms for the system

Publication

Tsung-Tso Hsieh, Che-Rung Lee: "Voda: A GPU Scheduling Platform for Elastic Deep Learning in Kubernetes Clusters", in IEEE International Conference on Cloud Engineering (IC2E), 2023

Education

National Tsing Hua University

Computer Science, M.S.

SCOPE Lab (Scientific Computing On Parallel Environment)

2019 - 2021

National Tsing Hua University

Double Major in Law and Computer Science, B.S.

2014 - 2018

履歷
個人檔案

Experience

Synopsys Inc.

Jan. 2022 - Present

Senior Software Engineer

VCS - Verilog Compile Simulator

C++, C, Compiler Optimization, Parallel Computing, Python

  • Developed and supported debug functionality for SystemVerilog compile simulator
  • Parallelized design traversal in FSDB waveform dumping, speeding up runtime by 3x with multithreading
  • Optimized FSDB gate-data loading and reduced 10-60% runtime memory footprint, benefiting customers running hundreds-of-GB designs with tight memory budgets
  • Initiated a project to migrate STL hash tables to Abseil Swiss tables for a millions-line code base, reducing up to 70% peak memory usage and speeding up hash table queries by 100%
  • Debugged and resolved urgent customer issues in tight timelines (< 1 day TAT) with limited information, tools, and access to the environment

MediaTek Inc.

July 2020 - Aug. 2020

Software Engineer Intern

C, Python, Machine Learning

  • Designed memory management algorithm & firmware for real-time embedded system
  • Introduced machine learning and data visualization to automate issue analysis, saving 90% of human effort

Projects

Voda Scheduler

Feb. 2021 - Nov. 2022

 https://github.com/heyfey/vodascheduler  

(30+ stars)

GPU scheduler for elastic/distributed deep learning workloads in Kubernetes cluster 

Golang, Python, Distributed Systems

  • Architected and built a GPU scheduler using microservices architecture on top of Kubernetes and various open-source projects
  • Sped up overall training time by 2.38x and increased cluster utilization by 1.4x with
    • State-of-the-art scheduling algorithms with resource elasticity
    • Topology-aware scheduling & worker migration to consolidate resources
  • Designed and implemented heterogeneous scheduling, auto-scaling, and fault-tolerant mechanisms for the system

Publication

Tsung-Tso Hsieh, Che-Rung Lee: "Voda: A GPU Scheduling Platform for Elastic Deep Learning in Kubernetes Clusters", in IEEE International Conference on Cloud Engineering (IC2E), 2023

Education

National Tsing Hua University

Computer Science, M.S.

SCOPE Lab (Scientific Computing On Parallel Environment)

2019 - 2021

National Tsing Hua University

Double Major in Law and Computer Science, B.S.

2014 - 2018