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4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
軟體工程師 @POMME Tech2023 ~ 2024
・
軟體工程師
一個月內
easy to sort Bin by count/rate. Planning and writing of software architecture design documents. Software personnel development schedule, software project working hours calculation planning. a. Finished project management system with team member. Discuss and develop software specifications with customers. Innostor Technology Corporation, software engineer, Dec 2008 ~ May 2013 Mass production test software development (including MP Tool, QC Tool, OEM Tool, Recovery... etc.). a. Hard disk partition encryption application. b. Production line mass production application. SMI, Software Engineer, Oct 2004 ~ Oct 2008 System H
就職中
・
正在積極求職中
全職 / 對遠端工作有興趣
15 年以上
元培科技大學
・
電子工程
軟體工程師 @鴻銘資訊有限公司2020 ~ 現在
・
軟體工程師
一個月內
王韋智 我是韋智，曾經任職軟體助理工程師一職，現在欲尋找軟體工程、網頁相關工作。 軟體工程師 Taichung，TW [email protected] 學歷 國立勤益科技大學, 學士學位, 資訊管理系, 2014 ~ 2018 高雄市立高雄高級工業職業學校, 高中文憑, 資訊科, 2011 ~ 2014 技能 前端技術 擅長 HTML5
就職中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
國立勤益科技大學
・
資訊管理系
曾任
軟體助理工程師 @逍遙有限公司2021 ~ 2024
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軟體工程師、全端工程師、前端工程師
一個月內
蔡福人 軟體助理工程師 台灣台中[email protected] 工作經歷 一月Present Taipei, Taiwan 軟體助理工程師 逍遙有限公司 公司網頁前端維護、網頁切版跟前端API資料串接 協助專案內容：軟件自動化測試，軟件前端美工與串接功能，網頁API串接，後端資料處理。 一年前開
待業中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
嶺東科技大學
・
科技商品設計系
曾任
Software Project Manager @Askey Computer Corp.(Asus Group), Taiwan,2020 ~ 2023
・
Project Manager、Software Project Manager、Product Manager
一個月內
release~2020) •Improving software project management process in Japan ODM project including reduce additional meeting with customer times (10/month to 4/month), reduce the SPEC misunderstanding communication time (save 60%) •Technical support for ODM/Customer Support projects. New Taipei City, Taiwan 工作經歷 Software Project Manager • Askey Computer Corp.(Asus Group), Taiwan, 六月十一月 2023 Software Project Management ‧ Marketing / ODM requirements (RFI/RFQ) gathering and analysis ‧ SPEC, Scope project plan management ‧ Risk plan management ‧ Problem solving ‧ Coordinate cross functional teams ‧ Software life cycle Management ‧ Rutine meeting with
待業中
・
正在積極求職中
全職 / 對遠端工作有興趣
10 到 15 年
Tamkang University
・
Water Resources and Environmental Engineering
Software Specialist @Elekta2020 ~ 現在
・
Senior Software Engineer
一個月內
Nguyen Quan Software Specialist at Elekta Hanoi, Công Hòa Xã Hội Chủ Nghĩa Việt Nam Experience with MS Windows OS as administrator Great experience with Microsoft system internal tools like Office 365 admin, SQL, Azure, support customer and agent of Microsoft. Basic knowledge about Linux. Experience in Support Treatment system (Mosaiq, Monaco...). Experience support end user, Ability of working in team or individually Friendly, keen on sport, music, and travel Looking for a higher duty and more challenging position. Kinh nghiệm làm việc Software Specialist • Elekta thángPresent - Customer Medical support - Troubleshooting software medical
就職中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
University of Information Technology
就職中
・
正在積極求職中
全職 / 對遠端工作有興趣
6 到 10 年
國立台北科技大學 NTUT
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Java & Android 人才培育專班
待業中
・
正在積極求職中
全職 / 對遠端工作有興趣
6 到 10 年
Universitas Teknokrat Indonesia
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Computer Science
軟體開發工程師 @中國信託證券2022 ~ 現在
・
iOS 工程師
一個月內
開發，維護，測試，修改 將 Objective c 程式轉為 swift 並加以重構 開發者帳號管理上架憑證到期更新，APP上架，上架退件處理 年代新聞台, 軟體開發工程師, 2017 / 7 ~ 2017 / 10 主要經手專案：瑞興銀行 工作內容：專案收尾並上架 醬子科技股份有限公司, 軟體開發工程
就職中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
財團法人資訊工程策進會
・
App 開發
曾任
Software Engineer @iKala2020 ~ 2023
・
Software Engineer
一個月內
Chiyuang Tseng Chiyuang [email protected] Skills Programming language: Go, Python, C++ Developing tool: Linux, Git, Docker, Kubernetes, Postman Databases: MySQL, Redis, MongoDB, Firestore, BigQuery Cloud: GCP(Kubernetes Engine, BigQuery, CloudSQL, Cloud Storage, Pub/Sub), AWS(SES, SNS) Others: Nginx, ELK stack, RESTful API, Swagger Experience FebDec 2023 Senior Software Engineer, iKala(CDP) OctJan 2023 Software Engineer, iKala(CDP) Designed and implemented an URL shortener for event tracking Designed and implemented IAM module of CDP Responsible for 3rd party API integrations, includes Google Ads, AWS SES&SNS, Newsleopard(email), MAAC(LINE messaging provider), and EVERY8D
待業中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
台灣大學
・
計算機科學最輕量、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。
- 瀏覽所有搜尋結果
- 每日可無限次數開啟陌生對話
- 搜尋僅開放付費企業檢視的履歷
- 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
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
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。
超過一年
Software Engineer Intern
Zscaler Softech India Private Limited
・
2021 ~ 現在
專業背景
目前狀態
就學中
求職階段
專業
後端開發人員
產業
軟體
工作年資
小於 1 年
管理經歷
技能
語言能力
English
・
專業
Hindi
・
母語或雙語
求職偏好
希望獲得的職位
Software Development Engineer
預期工作模式
兼職
期望的工作地點
Bangalore, Karnataka, India
遠端工作意願
對遠端工作有興趣
接案服務
否
學歷
學校
PES University
主修科系
B.Tech Computer Science and Engineering
Work Experience
Software Engineer Intern, May 2020 ~ Jul 2020
Zscaler Softech India Private Limited|
Achievements/Tasks
- Worked in Security team that applies security policies on data like Data Loss Prevention, URL classification using ML techniques and Cloud Sandboxing.
- My work revolved around understanding, improvising and contributing to several components of CASB(Cloud Access Security Broker) like refactoring some code components, automating information scrapping from vendor websites and supporting daily difference functionality, enhancing some scripts and writing preprocessing script to handle additional vendor data.
- Also added C code for small features like structure flattening for efficient processing of data and fetching and displaying data from predefined X-Macro in particular format.
- Tools and technologies used - Python scripting, C programming, Web Scraping, Object-Oriented Design, FreeBSD OS, Selenium WebDriver
Research Intern, Jun 2019 ~ Jul 2019
CDSAML, PES University|
Achievements/Tasks
- Scene Description using Densecap-Hybrid-Hierarchical RNN| - Generated image description in the form of coherent paragraphs using Densecap CNN for Dense Captioning and Hierarchical RNN on a subset of Visual Genome dataset consisting of around 20k images.
- Was able to perform as good as state-of-art in terms of Meteor score which is inclined towards human-like sentences.
- Tools and Technologies used - Python, TensorFlow, Deep Learning, Jupyter Notebook, Ubuntu
Education
B.Tech Computer Science and Engineering, 2017~2021
PES University, Bangalore - 9.42 / 10 CGPA
Courses: Cloud Computing, Data Analytics, Machine Learning, Web Technology
Intermediate, 2015 ~ 2017
Mata Kasturi Devi Public School, New Delhi - 90.8%
Matriculation, 2011 ~ 2015
St. Francis Xavier School, Hisar, Haryana - 10/10 CGPA
Skills
Industry Skills
Data Analytics
Data Structures and Algorithms
Problem Solving
Object Oriented Design
Database Management System
Programming & Web
Programming Languages:
C, C++, Python, SQL
Web Technology:
HTML, CSS, Javascript, PHP, AJAX, RESTful APIs
Others
Tools & Technologies:
Linux, Git
Spoken Languages:
English, Hindi
Projects
Code Semantic Detector|
- A Machine Learning based system to detect semantics/high-level function of code in the form of semantic label.
- Made to run on self-generated dataset of 500 programs across 25 labels from 8 DS/Algorithm categories.
- Approached in static and dynamic way giving accuracies of 98% and 80% respectively.
- Implemented using Python, TensorFlow, JQuery, Flask, Neural Networks, AST path mining, Universal Approximation Theorem, Naive Bayes Classifier.
RideShare on AmazonAWS|
- A scalable, distributed, fault-tolerant, highly-available, containerized and micro-services based ridesharing service deployed on AWS EC2.
- Implemented using Flask, Docker, Rabbit-MQ, Zookeeper, MySQL and RESTful APIs.
Farm-To-Fork|
- An ecommerce website for direct selling of farm goods by farmers to consumers involving Machine Learning techniques for suggestion and recommendation.
- Implemented using Jquery, Flask, MySQL, RESTful APIs and performed Unit, System and Performance tests.
Malware Detection on Microsoft’s Malware dataset|
- Predicting whether a Window’s machine will soon be hit with a malware using a Light Gradient Boosting Machine model.
- Obtained an AUC of 0.6712 and was scored 0.682 on Kaggle Submission.
- Implemented using Python, TensorFlow, Google Colaboratory.
Achievements
Currently hold Global Rank 36 on InterviewBit
Currently hold Institute Rank 3 out of 2130 on GeeksForGeeks
Stood at 4126/11,750 in Google Kick Start Round D 2020
Awarded Prof. CNR Rao Merit Scholarship in first 6 semesters for being in Top 20% of current CSE Batch at PES University
Extra Curricular
Attended Google’s Developer Student Club PESU (DSC PESU) Cloud Study Jam | QWIKLABS Profile|
Held at PES University, Bangalore on 20 July 2019
Participated in Microsoft’s MSHACK Hackathon|
Held at Microsoft IDC, Bangalore on 19-20 January 2019
Good Samaritans - Android Mobile app that lets users in distress seek help from other willing users in the vicinity.
Work Experience
Software Engineer Intern, May 2020 ~ Jul 2020
Zscaler Softech India Private Limited|
Achievements/Tasks
- Worked in Security team that applies security policies on data like Data Loss Prevention, URL classification using ML techniques and Cloud Sandboxing.
- My work revolved around understanding, improvising and contributing to several components of CASB(Cloud Access Security Broker) like refactoring some code components, automating information scrapping from vendor websites and supporting daily difference functionality, enhancing some scripts and writing preprocessing script to handle additional vendor data.
- Also added C code for small features like structure flattening for efficient processing of data and fetching and displaying data from predefined X-Macro in particular format.
- Tools and technologies used - Python scripting, C programming, Web Scraping, Object-Oriented Design, FreeBSD OS, Selenium WebDriver
Research Intern, Jun 2019 ~ Jul 2019
CDSAML, PES University|
Achievements/Tasks
- Scene Description using Densecap-Hybrid-Hierarchical RNN| - Generated image description in the form of coherent paragraphs using Densecap CNN for Dense Captioning and Hierarchical RNN on a subset of Visual Genome dataset consisting of around 20k images.
- Was able to perform as good as state-of-art in terms of Meteor score which is inclined towards human-like sentences.
- Tools and Technologies used - Python, TensorFlow, Deep Learning, Jupyter Notebook, Ubuntu
Education
B.Tech Computer Science and Engineering, 2017~2021
PES University, Bangalore - 9.42 / 10 CGPA
Courses: Cloud Computing, Data Analytics, Machine Learning, Web Technology
Intermediate, 2015 ~ 2017
Mata Kasturi Devi Public School, New Delhi - 90.8%
Matriculation, 2011 ~ 2015
St. Francis Xavier School, Hisar, Haryana - 10/10 CGPA
Skills
Industry Skills
Data Analytics
Data Structures and Algorithms
Problem Solving
Object Oriented Design
Database Management System
Programming & Web
Programming Languages:
C, C++, Python, SQL
Web Technology:
HTML, CSS, Javascript, PHP, AJAX, RESTful APIs
Others
Tools & Technologies:
Linux, Git
Spoken Languages:
English, Hindi
Projects
Code Semantic Detector|
- A Machine Learning based system to detect semantics/high-level function of code in the form of semantic label.
- Made to run on self-generated dataset of 500 programs across 25 labels from 8 DS/Algorithm categories.
- Approached in static and dynamic way giving accuracies of 98% and 80% respectively.
- Implemented using Python, TensorFlow, JQuery, Flask, Neural Networks, AST path mining, Universal Approximation Theorem, Naive Bayes Classifier.
RideShare on AmazonAWS|
- A scalable, distributed, fault-tolerant, highly-available, containerized and micro-services based ridesharing service deployed on AWS EC2.
- Implemented using Flask, Docker, Rabbit-MQ, Zookeeper, MySQL and RESTful APIs.
Farm-To-Fork|
- An ecommerce website for direct selling of farm goods by farmers to consumers involving Machine Learning techniques for suggestion and recommendation.
- Implemented using Jquery, Flask, MySQL, RESTful APIs and performed Unit, System and Performance tests.
Malware Detection on Microsoft’s Malware dataset|
- Predicting whether a Window’s machine will soon be hit with a malware using a Light Gradient Boosting Machine model.
- Obtained an AUC of 0.6712 and was scored 0.682 on Kaggle Submission.
- Implemented using Python, TensorFlow, Google Colaboratory.
Achievements
Currently hold Global Rank 36 on InterviewBit
Currently hold Institute Rank 3 out of 2130 on GeeksForGeeks
Stood at 4126/11,750 in Google Kick Start Round D 2020
Awarded Prof. CNR Rao Merit Scholarship in first 6 semesters for being in Top 20% of current CSE Batch at PES University
Extra Curricular
Attended Google’s Developer Student Club PESU (DSC PESU) Cloud Study Jam | QWIKLABS Profile|
Held at PES University, Bangalore on 20 July 2019
Participated in Microsoft’s MSHACK Hackathon|
Held at Microsoft IDC, Bangalore on 19-20 January 2019
Good Samaritans - Android Mobile app that lets users in distress seek help from other willing users in the vicinity.