CakeResume 找人才
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On
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
一個月內
就職中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
國立政治大學（National Chengchi University）
・
資訊科學系曾任
Data Engineer @Rooit Inc. (XO App)2023 ~ 2023
・
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
一個月內
待業中
・
正在積極求職中
全職 / 對遠端工作有興趣
6 到 10 年
中國醫藥大學(China Medical University)
・
臨床醫學研究所
OPC Chief Engineer @TSMC2020 ~ 現在
・
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
一個月內
Chun-Jung Huang [email protected] Chiao-Tung University, Ph.D. - Photonics,2015 ~ 2020 Member of The Phi Tau Phi Scholastic Honor Society of the Republic of China. Work Experience TSMC, OPC Chief Engineer (MarPresent) ◆Introduced image anomaly detection techniques to identify and address defects in photomask manufacturing, significantly improving product quality and reducing turnaround time. ◆Managed large-scale data processing tasks, demonstrating expertise in analyzing and handling datasets of hundreds of millions, to bolster model development and optimization. ◆Excelled in distributed computing, optimizing code execution across thousands of systems to
就職中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
National Chiao-Tung University
・
Ph.D. - Clinical Engineering
智慧製造全端開發工程師 @聯華電子股份有限公司2022 ~ 現在
・
AI工程師、機器學習工程師、深度學習工程師、影像演算法工程師、資料科學家、Ai Application Engineer,Machine Learning Engineer,Deep Learning Engineer,Data Scientist
一個月內
潘揚燊 ㄕㄣ Shen Pan Kaohsiung City，Taiwan • [email protected] 希望職務：人工智慧、機器視覺應用開發工程師 現任 : 聯華電子 RPA 平台全端開發工程師 您好，我是潘揚燊，目前任職於 聯華電子 ， 擔任 智慧製造 全端開發工程師 ， 畢業於元智大學工業工程與管理學系研
就職中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
元智大學 Yuan Ze University
・
工業工程與管理學系所
Senior engineer @Chicony Electronics Co, Ltd.2018 ~ 現在
・
全端工程師、後端工程師、前端工程師、軟體專案主管、AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
一個月內
Nelson Chen Senior engineer Dedicated Software Engineer with 6+ Years of Experience Senior software engineer specializing in web page development and deep learning. Proficient with machine learning technologies, such as TensorFlow, Numpy, etc. Experience Senior engineer • Chicony Electronics Co, Ltd. ．Build an Auto-Encoder AI model for defective detection. ．Build an object detection model for detecting car types. ．Developed a Front-End and Back-End website for data analysis. ．Manage the production process and make it automated production. NovPresent Software engineer • Teco image systems co. ltd ．Developed and maintained MFP driver
就職中
・
正在積極求職中
全職 / 對遠端工作有興趣
6 到 10 年
National Taiwan Ocean University
・
Computer science and engineering就職中
・
正在積極求職中
全職 / 對遠端工作有興趣
6 到 10 年
清華大學 National Tsing Hua University
・
核子工程 nuclear engineering
Research & Development Engineer @三竹資訊股份有限公司2023 ~ 現在
・
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
一個月內
following experience： - backend framework: Spring boot, Flask - familiar with DB syntax for Elasticsearch, PosgresSQL and MSSQL Taiwan E-mail: [email protected] Skill languages Python JAVA backend Spring Boot Flask Deep Learning Pytorch CI/CD Docker Git SVN Jenkins Work Experience 工作經歷 Research & Development Engineer Mitake Information Corporation • JulPresent LLM-Based conversation system R&D Retrival Augmented Generation (RAG) system development ReAct prompting system development OpenSource LLM inference/prompting engineering Software Engineer Gorilla Technology Group • OctMay 2023 Main Role / Achievement: Research machine learning topics such as natural language processing (NLP) and deep
就職中
・
目前會考慮了解新的機會
全職 / 暫不考慮遠端工作
4 到 6 年
國立中央大學 National Central University
・
資訊工程
資訊人員 @新北市淡水區公所2023 ~ 現在
・
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
一個月內
謝慧珊 目前就職於公家機關擔任資訊人員，熱愛閱讀與寫作， 即將於致理科技大學進修商務智慧與創新科技研究所碩士班， 研究範圍為AI創新科技領域。 個性情感充沛並且喜歡觀察人群與反思，勇於接受挑戰。 座右銘： 樂觀積極，感恩惜福 www.shammixxd159
就職中
・
目前會考慮了解新的機會
全職 / 我只想遠端工作
10 到 15 年
致理科技大學
・
資訊管理系
Senior Software Engineer @International Integrated Systems, Inc.(IISI)2020 ~ 現在
・
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
一個月內
Chin Ya Chang Machine Learning Engineer New Taipei City , Taiwan [email protected] Current Position: AI Team - Software Engineer at the Central Weather Bureau, specializing in machine learning. Tasks include image generation, numerical prediction, data calibration, recommendation systems, and text generation using data from satellites, radar, and geographic information. I stay updated on AI advancements by studying research papers and implementing new approaches into projects. Recently, I've focused on deploying Large Language Models (LLM) in customer-oriented chatbots. Proficient in Docker for establishing and maintaining development environments, deploying projects to client environments.
就職中
・
目前會考慮了解新的機會
全職 / 對遠端工作有興趣
4 到 6 年
私立中原大學 Chung Yuan Christian University
・
環境工程
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
兩個月內
Top 10 trang cá độ bóng đá uy tín nhắt Việt Nam. Review nền tảng cá cược trực tuyến cho những ai chưa tìm được web cá độ qua mạng phù hợp 351 Đ. Lê Đại Hành, Phường 13, Quận 11, Thành phố Hồ Chí Minh, Việt Nam#trangcacuocbongda #Trang_Cá_Độ_Bóng_Đá #Trang_Cá_Cược_Bóng_Đá https://trangcacuocbongda.app/ https://www.youtube.com/channel/UCoJT7RDFAl5RfBiA0tUtMYg/about https://www.reddit.com/user/trangcacuocbongdaapp/ https:/
就學中
・
目前會考慮了解新的機會
兼職 / 暫不考慮遠端工作
4 到 6 年
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。
專業背景
目前狀態
就職中
求職階段
目前沒有興趣尋找新的機會
專業
機器學習工程師, 數據科學家
產業
人工智慧 / 機器學習, 大數據, 軟體
工作年資
2 到 4 年
管理經歷
我有管理 1～5 人的經驗
技能
語言能力
English
・
專業
求職偏好
希望獲得的職位
Machine Learning Engineer
預期工作模式
全職
期望的工作地點
台灣台北, 台灣台南市, 美國加利福尼亞洛杉磯, 德國慕尼黑, 加拿大安大略多倫多
遠端工作意願
對遠端工作有興趣
接案服務
否
學歷
學校
NCKU, Master Degree
主修科系
Computer Science
Kai-Chou, Yang
As a Kaggle Competition Master and a winner of international data science challenges, I am experienced in machine learning, deep learning and related frameworks such as PyTorch.
My research focuses on natural language processing (NLP), where I have released 11 open-source projects such as MianBot (700+★ on Github) and presented certain academic papers on top conferences like ACL, AAAI, CIKM, and WSDM.
International Awards
For the following achievements, I am the first author as well as the team leader.
2nd Place, CIKM Cup: Cross-lingual Short-text Matching Challenge
- Proposed two densely-connected architectures, CPRNN and DACNN, for sentence pair modeling.
- Fused semantic features from different levels to create diversity intra-models.
- The solution has been oral presented on CIKM 2018 in Turin, Italy.
3rd Place, WSDM Cup: Fake News Classification Challenge
- Implemented various NLI networks like ESIM and injected world knowledge using BERT.
- Proposed a disagreement-aware model based on the single-word attention.
- The paper has been oral presented on WSDM 2019 in Melbourne, Australia.
4th place, Google AI: Gendered Pronoun Resolution Competition
- Leveraged the information redundancy from BERT and extracted features from the optimal layer.
- Proposed a multi-heads Siamese semantic scorer for answer selection.
- The paper has been presented on ACL 2019 in Florence, Italy.
Kaggle Competition Master, Ranked top 0.2% (233/114,366)
- Top 1% (4/838), Gendered Pronoun Resolution Competition.
- Top 1% (27/4,550), Toxic Comment Classification Challenge.
- Top 3% (30/1,449), CareerCon 2019 - Help Navigate Robots.
- Top 4% (103/3,165), Jigsaw Unintended Bias in Toxicity Classification.
- Top 6% (223/3,633), CommonLit Readability Prize.
- Top 10% (384/3,946), TalkingData AdTracking Fraud Detection Challenge.
Work Experience
Taiwan AI Labs, Machine Learning Engineer, Sep 2019 ~ Now
Question Answering System
- Propose a conditional question generator with mT5 for controllable QA data augmentation and as the base of dense retrieval, which improves recall@50 from baseline model by 16%.
- Build a generative pseudo labeling pipeline using a open-domain passage retriever and machine reader, which improve the nDCG@10 by 4.2 - 9.7, on various domains.
- Build an efficient passage re-ranker based on tiny-bert with a time-series based clustering framework for effective negative passage sampling.
- Leverage FinBERT on QA analysis and slot filling for fintech dialogue system.
Natural Language Understanding
- Implement a document encoder with self-contrastive learning and a document clustering algorithm, which is scalable for million scale of streaming data.
- Implement a GROVER-like generator as the backbone for topic detection, article rewriting, and tag generation.
- Propose a semi-automatic framework for fake-news identification, which gathers evidence from event properties, user behavior and textual features.
- Propose a SOTA Chinese typo correction system based on a boosting loop of automatic speech recognition and text to speech for weak supervision.
- Build a general-purpose NLP training pipeline for team use involving data augmentation, data regularization, and unsupervised domain adaptation.
Education
Master in Department of Computer Science, NCKU GPA: 4.30
- Honorary member of the Phi Tau Phi Scholastic Honor Society. (Ranked 1st among all graduates.)
- As a teaching assistant for Introduction to Data Science, Data Mining and Discrete Mathematics.
- As a speaker / teaching assistant for introduction lectures of machine learning.
Bachelor in Department of Computer Science, NCKU GPA: 3.92
- Academic excellence awards 2016.
- Academic excellence awards 2015.
- Honorable mention on the graduation exhibition.
- Research assistant on a question answering system project for the Ministry of Science and Technology.
Side Projects
I list some of my project experiences. You can refer to my Github for the other interesting ideas.
Mianbot
- Got 700+ stars and 200+ forks on Github.
- Implemented the hierarchical keywords matching using word2vec.
- Implemented the IR-based searching module to support chit-chat.
- Allow user to define customized scenarios with JSON.
- The extracted QA pairs were released in PTT-Gossiping-Dataset, a widely-used Chinese chit-chat corpus.
NCKU Smart-Life LineBot
- A Linebot that helps solve trivial matters such as restaurant recommendation.
- The dialogue system is based on LUIS for intent classification.
- The backend was built with Django / Flask (new version) and host on Heroku.
- The backend is connected with Line server using the web API.
Knowledge & Skills
- General Machine Learning
- Classification, Regression, Clustering, Boosting, Feature Engineering.
- Natural Language Processing
- Sentence Pair Modeling: Natural language Inference, Machine Reading Comprehension, Sentence Similarity
- Text Classification / Regression / Clustering
- Deep contextual representation (ELMO / BERT / XLNet / ELECTRA / RoBERTa / ERINE2.0 / BigBird / T5)
- Recommendation System
- Factorization: Matrix Factorization, Factorization Machine, DeepFM
- Graph Embedding: DeepWalk, Node2Vec, item2Vec
Publication
- Fake News Detection as Natural Language Inference. Kai-Chou Yang; Timothy Niven; Hung-Yu Kao. WSDM Cup 2019
- Fill the GAP: Exploiting BERT for Pronoun Resolution. Kai-Chou Yang; Timothy Niven; Tzu Hsuan Chou; Hung-Yu Kao. ACLWS'19
- Generalize Sentence Representation with Self-Inference. Kai-Chou Yang; Hung-Yu Kao. AAAI 2020
- The Prevalence and Impact of Fake News on COVID-19 Vaccination in Taiwan: A Retrospective Study of Digital Media. Yen-Pin Chen; Yi-Ying Chen; Kai-Chou Yang; Feipei Lai; Chien-Hua Huang; Yun-Nung Chen; Yi-Chin Tu. JMIR
Kai-Chou, Yang
As a Kaggle Competition Master and a winner of international data science challenges, I am experienced in machine learning, deep learning and related frameworks such as PyTorch.
My research focuses on natural language processing (NLP), where I have released 11 open-source projects such as MianBot (700+★ on Github) and presented certain academic papers on top conferences like ACL, AAAI, CIKM, and WSDM.
International Awards
For the following achievements, I am the first author as well as the team leader.
2nd Place, CIKM Cup: Cross-lingual Short-text Matching Challenge
- Proposed two densely-connected architectures, CPRNN and DACNN, for sentence pair modeling.
- Fused semantic features from different levels to create diversity intra-models.
- The solution has been oral presented on CIKM 2018 in Turin, Italy.
3rd Place, WSDM Cup: Fake News Classification Challenge
- Implemented various NLI networks like ESIM and injected world knowledge using BERT.
- Proposed a disagreement-aware model based on the single-word attention.
- The paper has been oral presented on WSDM 2019 in Melbourne, Australia.
4th place, Google AI: Gendered Pronoun Resolution Competition
- Leveraged the information redundancy from BERT and extracted features from the optimal layer.
- Proposed a multi-heads Siamese semantic scorer for answer selection.
- The paper has been presented on ACL 2019 in Florence, Italy.
Kaggle Competition Master, Ranked top 0.2% (233/114,366)
- Top 1% (4/838), Gendered Pronoun Resolution Competition.
- Top 1% (27/4,550), Toxic Comment Classification Challenge.
- Top 3% (30/1,449), CareerCon 2019 - Help Navigate Robots.
- Top 4% (103/3,165), Jigsaw Unintended Bias in Toxicity Classification.
- Top 6% (223/3,633), CommonLit Readability Prize.
- Top 10% (384/3,946), TalkingData AdTracking Fraud Detection Challenge.
Work Experience
Taiwan AI Labs, Machine Learning Engineer, Sep 2019 ~ Now
Question Answering System
- Propose a conditional question generator with mT5 for controllable QA data augmentation and as the base of dense retrieval, which improves recall@50 from baseline model by 16%.
- Build a generative pseudo labeling pipeline using a open-domain passage retriever and machine reader, which improve the nDCG@10 by 4.2 - 9.7, on various domains.
- Build an efficient passage re-ranker based on tiny-bert with a time-series based clustering framework for effective negative passage sampling.
- Leverage FinBERT on QA analysis and slot filling for fintech dialogue system.
Natural Language Understanding
- Implement a document encoder with self-contrastive learning and a document clustering algorithm, which is scalable for million scale of streaming data.
- Implement a GROVER-like generator as the backbone for topic detection, article rewriting, and tag generation.
- Propose a semi-automatic framework for fake-news identification, which gathers evidence from event properties, user behavior and textual features.
- Propose a SOTA Chinese typo correction system based on a boosting loop of automatic speech recognition and text to speech for weak supervision.
- Build a general-purpose NLP training pipeline for team use involving data augmentation, data regularization, and unsupervised domain adaptation.
Education
Master in Department of Computer Science, NCKU GPA: 4.30
- Honorary member of the Phi Tau Phi Scholastic Honor Society. (Ranked 1st among all graduates.)
- As a teaching assistant for Introduction to Data Science, Data Mining and Discrete Mathematics.
- As a speaker / teaching assistant for introduction lectures of machine learning.
Bachelor in Department of Computer Science, NCKU GPA: 3.92
- Academic excellence awards 2016.
- Academic excellence awards 2015.
- Honorable mention on the graduation exhibition.
- Research assistant on a question answering system project for the Ministry of Science and Technology.
Side Projects
I list some of my project experiences. You can refer to my Github for the other interesting ideas.
Mianbot
- Got 700+ stars and 200+ forks on Github.
- Implemented the hierarchical keywords matching using word2vec.
- Implemented the IR-based searching module to support chit-chat.
- Allow user to define customized scenarios with JSON.
- The extracted QA pairs were released in PTT-Gossiping-Dataset, a widely-used Chinese chit-chat corpus.
NCKU Smart-Life LineBot
- A Linebot that helps solve trivial matters such as restaurant recommendation.
- The dialogue system is based on LUIS for intent classification.
- The backend was built with Django / Flask (new version) and host on Heroku.
- The backend is connected with Line server using the web API.
Knowledge & Skills
- General Machine Learning
- Classification, Regression, Clustering, Boosting, Feature Engineering.
- Natural Language Processing
- Sentence Pair Modeling: Natural language Inference, Machine Reading Comprehension, Sentence Similarity
- Text Classification / Regression / Clustering
- Deep contextual representation (ELMO / BERT / XLNet / ELECTRA / RoBERTa / ERINE2.0 / BigBird / T5)
- Recommendation System
- Factorization: Matrix Factorization, Factorization Machine, DeepFM
- Graph Embedding: DeepWalk, Node2Vec, item2Vec
Publication
- Fake News Detection as Natural Language Inference. Kai-Chou Yang; Timothy Niven; Hung-Yu Kao. WSDM Cup 2019
- Fill the GAP: Exploiting BERT for Pronoun Resolution. Kai-Chou Yang; Timothy Niven; Tzu Hsuan Chou; Hung-Yu Kao. ACLWS'19
- Generalize Sentence Representation with Self-Inference. Kai-Chou Yang; Hung-Yu Kao. AAAI 2020
- The Prevalence and Impact of Fake News on COVID-19 Vaccination in Taiwan: A Retrospective Study of Digital Media. Yen-Pin Chen; Yi-Ying Chen; Kai-Chou Yang; Feipei Lai; Chien-Hua Huang; Yun-Nung Chen; Yi-Chin Tu. JMIR