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4-6 years
6-10 years
10-15 years
More than 15 years
United States
智慧製造全端開發工程師 @聯華電子股份有限公司2022 ~ Present
・
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、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
Within one month
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
Employed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
元智大學
・
工業工程與管理學系所
Data Engineer @Groundhog Technologies Inc.2021 ~ 2024
・
Data Analyst、Data Engineer、Data Scientist、Customer Experience Analyst
Within one month
client procurement efficiency by 15% and increased deployment rates by 60%, demonstrating my ability to leverage data insights to drive business improvements. With a Master's in Information Management and a Bachelor's in Economics, I possess a deep understanding of the data lifecycle, from mining and visualization to machine learning and statistical analysis, using tools like PowerBI, Seaborn, and Tableau. My specialized skills in Time Series Analysis and Machine Learning are complemented by practical experience in data workflow management platforms, such as Airflow. I am proficient in English, which has been invaluable in my work within
Employed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
University of Illinois at Urbana-Champaign, School of Information Sciences
・
Information Management
Past
Marketing Associate @Shopback Inc.2023 ~ 2024
・
Digital Marketing
Within two months
表，並 提出改善方案 與設計新測試機制，優化CRM與行銷活動表現，以達設定目標。 [優化CRM] ：透過實際測試不同metrics的CRM incentive，與搭配machine learning的結果，提案優化 order programme 。 [KOC合作] ：與 160位以上KOC合作 ，配合相關行銷活動與品牌排程，透過人數的累積以達曝光KPI。 Sr. US
Unemployed
・
Ready to interview
Full-time / Remote Only
6-10 years
Sprott-Shaw College
・
Business management diploma
AI Engineer @Playsee2022 ~ Present
・
資料分析師、資料科學家、產品經理
Within one month
李昀庭 Data scientist Taiwan 技能 Machine learning and Engineering skills: Python, Big Query, Google Storage, Linux, Docker, GCP, AWS, Scikit-learn, Tensorflow, Pytorch, MLOps, FastAPI, Machine Learning, Deep Learning, Computer Vision, NLP Experimental design, Project management, Product design English - TOEIC 725 工作經歷 AI工程師 Playsee NovPresent Taipei, Taiwan 自動化標註推薦系統 設計並實踐架構取代25個標註者並及時標記和篩選視頻審核內容。 設計並優化影片
Employed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
National Cheng Kung University
・
心理所（認知科學所）
Sr. Inspection Process Engineer @Corning Incorporated2018 ~ Present
・
Technical support engineer
Within two months
quality issues through analysis of inspection results, HMI messages, system log/config files and parameter sets . ．Provid assistance to first-line support e ngineers who are unable to fix optical, electro, system hardware/software and database problems. ．I ndependent work of camera module installation/ alignment, machine parts replacement, software upgrade, system calibration and defect qualification. ．Build procedure documents for inspection issue troubleshooting, parts installation, system calibration and computer rebuild. Project manager ．Improve key performance indicators through DMAIC and Six-sigma approaches (Decrease cycle time 12.5% to save US$2,793K/year
Ready to interview
Full-time / Interested in working remotely
10-15 years
National Sun Yat-sen University
・
Computer Science, Data mining, Database modeling
商業分析師 @凱基商業銀行股份有限公司2021 ~ Present
・
Data Analyst、Data Engineer、Data Scientist、Customer Experience Analyst
Within one month
Employed
・
Open to opportunities
Full-time / Interested in working remotely
4-6 years
國立政治大學（National Chengchi University）
・
數位內容
Principal @Cascade Data Labs2016 ~ 2022
・
Director Data
Within two months
Emily Ledoux Delivery Principal Seasoned Delivery Principal in the Data Practice. Focused on designing robust, scalable data ecosystems in the cloud to feed insights and data visualizations. Well-rounded consultant with experience spanning sales, recruiting, and delivery. Proven Delivery & Client Lead. Portland, OR, USA https://www.linkedin.com/in/emily-ledoux/ Work Experience JanuaryPresent Principal Data Architect Kin + Carta Delivery or Client Lead for over 25 resources, including direct reports, delivery oversight, hours tracking, QBRs, onboarding management, budget ownership and related responsibilities. Cloud Architect, designing Azure and
Employed
・
Open to opportunities
Full-time / Interested in working remotely
6-10 years
University of Pennsylvania
・
EconomicsSenior Analyst, Software Engineer @Synpulse Taiwan Ltd. | 星普思管理諮詢有限公司2022 ~ Present
・
Software Developer
Within one month
Employed
・
Open to opportunities
Full-time / Interested in working remotely
4-6 years
Queensland University of Technology(昆士蘭科技大學)
・
Computer Science安全組組長 @INTECHWORLD INC.(菲律賓總公司）（電腦系統整合服務業）2022 ~ Present
・
滲透測試、資訊安全
Within one month
Employed
・
Open to opportunities
Full-time / Interested in working remotely
4-6 years
資策會
・
雲端網路系統工程師
Senior Machine Learning Engineer @CoolSo2020 ~ Present
・
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
Within one month
許碩文 / Shuo-Wen (Peter) Hsu Senior Machine Learning Engineer at CoolSo / Berkeley SkyDeck Batch15 Alumni - Machine learning expert with 5+ years' experience - Engaged in different fast-paced environments with various leadership roles including CTO - Former senior chip/system designer with 5+ years' experience - Energetic engineer pursuing adventures in AI/ML career Nangang District, Taipei City, Taiwan 115 Tel:EMail: [email protected] Work Experience Senior Machine Learning Engineer • CoolSo Technology CoolSo is a startup team builds gesture recognition through machine learning technologies uses only commercial grade sensors could be found
Full-time / Interested in working remotely
4-6 years
University of California, Berkeley
・
Business/Commerce, GeneralThe Most Lightweight and Effective Recruiting Plan
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Definition of Reputation Credits
Technical Skills
Specialized knowledge and expertise within the profession (e.g. familiar with SEO and use of related tools).
Problem-Solving
Ability to identify, analyze, and prepare solutions to problems.
Adaptability
Ability to navigate unexpected situations; and keep up with shifting priorities, projects, clients, and technology.
Communication
Ability to convey information effectively and is willing to give and receive feedback.
Time Management
Ability to prioritize tasks based on importance; and have them completed within the assigned timeline.
Teamwork
Ability to work cooperatively, communicate effectively, and anticipate each other's demands, resulting in coordinated collective action.
Leadership
Ability to coach, guide, and inspire a team to achieve a shared goal or outcome effectively.
Professional Background
Current status
Employed
Job Search Progress
Not open to opportunities
Professions
Machine Learning Engineer, Data Scientist
Fields of Employment
Artificial Intelligence / Machine Learning, Big Data, Software
Work experience
2-4 years
Management
I've had experience in managing 1-5 people
Skills
Languages
English
・
Professional
Job search preferences
Positions
Machine Learning Engineer
Job types
Full-time
Locations
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
Remote
Interested in working remotely
Freelance
No
Educations
School
NCKU, Master Degree
Major
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