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On
4-6 years
6-10 years
10-15 years
More than 15 years
Taiwan
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
reducing parameter training volume to 2% , decreasing memory usage by 70%, and increasing training speed by 25%. Architecture Optimization: Used Direct Preference Optimization (DPO) to optimize Reinforcement Learning, improving model efficiency and decision quality. [ G itHub ] Graduate Research Assistant OctOct 2023 Institute of Information Science, Academia Sinica, Taiwan Natural Language and Knowledge Processing Lab (NLP Lab) Publication: Published in ACM CIKMSequential Text-based Knowledge Update with Self-Supervised Learning for Generative Language Models . [ Paper | GitHub ] Performance has improved by 18.8% compared to traditional methods in the past and surpassed SOTA LLMs by 39.6
Employed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
國立政治大學（National Chengchi University）
・
資訊科學系
Research & Development Engineer @三竹資訊股份有限公司2023 ~ 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
趙啟雲 chiyun chao A software engineer with 4 years of experience in AI model training and backend development. In the domain of machine/deep learning, I am familiar with: - focus on NLP(Natural language processing) and DPI(Deep packet inspection) - NLP networks such as Transformer, BERT, T5 - have experience with AI training platform development with mlflow, Label Studio, DVC In terms of backend development, I have the 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
Employed
・
Open to opportunities
Full-time / Not interested in working remotely
4-6 years
國立中央大學 National Central University
・
資訊工程
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
Android Team Lead @104 Corporation2018 ~ Present
・
Senior Software Engineer, Principal Software Engineer, Engineering Manager
Within two months
incorporating: - A clean architectural approach - Integration with Firebase services - Support for the latest Android features ensuring scalability for future organizational growth - Successfully retained a 4.6-star user rating and boosted job application rates by 10%. • AI Implementation: Created an AI tool to convert UI test cases from natural language into UiAutomator2 scripts, seamlessly integrating them into the CICD process. This resulted in a 90% acceleration UiAutomator2 test case generation. • Technology Introduction: - Flutter: Developed an in-house App Dashboard to consolidate Android/iOS/backend CICD build statuses and test report outcomes. Single-handedly
Employed
・
Open to opportunities
Full-time / Interested in working remotely
More than 15 years
UNSW
・
Computer software, network and security engineeringPast
iOS Engoneer @VoiceTube 紅點子科技股份有限公司2020 ~ 2023
・
iOS Developer
Within three months
Unemployed
・
Open to opportunities
Full-time / Interested in working remotely
6-10 years
國立臺北大學 National Taipei University
・
資工所Data Engineer @MediaTek Inc.2019 ~ Present
・
Senior Software Engineer
Within one month
Employed
・
Open to opportunities
Full-time / Interested in working remotely
6-10 years
National Tsing Hua University
・
Data Mining, Database System
Engineering Manager @Viscovery 創意引晴股份有限公司2018 ~ Present
・
Within one month
including Recurrent Neural Network (RNN), word2vec, paragraph vector. Working Experience Intern, JulDec 2014 Phalanx Biotech Develop machine learning solutions for cancer gene detection and TSMC semiconductor quality prediction. Intern, JulAug 2013 Solid State System Assisted in CMOS MEMs microphone product development including proto-type simulation, fabrication/packaging process, defect analysis and market survey. Achievements 1. Qualified of preliminary contest of TSMC Big Data Analytics for Semiconductor Manufacturing. Taiwan,Completion of Broad-DREAM Gene Essentiality Prediction Challenge, 2014 Professional Skills Research Field Machine Learning Deep Learning Computer Vision Natural Language Processing Lang...
Employed
・
Open to opportunities
Full-time / Interested in working remotely
4-6 years
國立台灣大學
・
Electrical Engineering
Blockchain Enginner & AI Lead @Portal Network
Blockchain engineer & Blockchain consulting
Within one month
expressions, enhancing user interaction experiences. Emotion Recognition Systems: Developing AI systems capable of understanding and responding to user emotions, used to enhance customer service and user interactions. Voice Technology (TTS): Natural Voice Generation: Employing Text-to-Speech (TTS) technology to convert text into natural, fluent voice across multiple languages, suitable for virtual assistants and customer service bots. Voice Interaction Interfaces: Developing voice interaction interfaces that enable digital personas to conduct natural dialogues, offering more humanized interaction methods. Large Language Models and Natural Language Processing: Personalized Response Generation: Leveraging personality-driven large language models to provide customized
Full-time / Interested in working remotely
4-6 years
Senior Product Growth Manager @SOSV2018 ~ 2023
・
Product Manager / Product Growth
Within one month
and honed my skills in dynamic tech stacks. As a seasoned product manager, I've successfully navigated the intersection of user needs and technical innovation, steering product strategies for optimal growth. From leading software teams at IBM to co-founding a startup that delved into machine learning and natural language processing, I bring a unique blend of technical prowess, product expertise, and entrepreneurial flair. My expertise in growth hacking working with early stage startups around the world involves leveraging lean startup methodologies and data-driven decision-making to drive business success. I'm excited to bring
Employed
・
Not open to opportunities
Full-time / Interested in working remotely
10-15 years
Quantic School of Business and Technology
人工智慧工程師 @玉山銀行智能金融處 (Intelligent Finance Dept., E-SUN Bank )2020 ~ Present
・
Machine Learning Researcher / Engineer
Within one month
Jeffrey Lin ( 林奕勳 ) ESUN Bank, Intelligent Finance Technology Department, AI Engineer focusing on Enterprise-Level ML Frameworks and Design Patterns [email protected] TW, Taipei CAREER SUMMARY 6+ years of deep learning research and development experience, with a strong ability in prototyping, evaluation, and deployment of models, in both academical and industrial environment. 2+ years of financial AI development experience, specialized in the design of python API, SDK, and framework for optimizing the deployment flow of data science, ETL, and machine learning pipelines. 1+ year of participation in the technology management
Employed
Full-time / Interested in working remotely
4-6 years
National Taiwan University
・
Graduate Institute of Communication EngineeringThe Most Lightweight and Effective Recruiting Plan
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Data Scientist, Machine Learning Engineer
Fields of Employment
Work experience
4-6 years
Management
I've had experience in managing 5-10 people
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School
Major
Ryan Chao
[email protected] • 0978903016 • Taipei, Taiwan
Hi, I'm Ryan, my current research interests include natural language processing, data engineering, machine learning and data related applications, and these are also my daily duties.
Experience
PIXNET
Assistant Manager, Aug 2020 - Sep 2022
- Lead data team(Aug 2020 - now)
Lead and manage data team with 6 members, we are dedicated to deliver insights from data to the company, not only support decision-making for business but also provide tech solutions to our services and products. My contributions includes:
- Architecture and methodology review for data solutions and various data analytic tasks
- Translate abstract business problems into solvable engineering components
- Project planning and management
- Goal alignment
Advanced Algorithm Engineer, Oct 2017 - Aug 2020
- Data streaming system development for near real time user tagging (Jan 2020 - Jul 2020)
A kubernetes based application aims to link our content delivery system to the online readers according to their real time behaviors.
- I lead the system architecture design
- Handle concurrent traffic from over 5M users everyday
- Leverage google cloud services such as GKE, GAE, and Pub/Sub.
- General algorithm development in large scale (Oct 2017 - now)
Deep learning is fascinating, I was a member of "Deep learning 101 Study Group" and learned a lot from there. However, in practical scenarios, it's surprising to see some fundamental algorithms can show us more insights. - PySpark dataframe programming
- Recommendation algorithm design, improved and achieved the best performance at that time
- Various classification tasks
- User profile construction with NLP.
- Information retrieval based chat bot
- Data warehousing and ETL management (Feb 2019 - now)
I created some tools(e.g., airfly) to help us management our data more efficiently.
- Based on PySpark
- Auto DAG generator: automatically resolve and build the task dependencies for our data pipeline
- Metadata management.
- More easier to perform data analytics such as EDA, data mining, machine learning tasks, etc.
- BI platform development (April 2019 - Oct 2019)
- Leverage Google Dataproc to handle large scale adhoc queries for business team.
- Provide daily user demographics, metrics and reports with datastudio.
- Tech lead of our 5th PIXNET HACKATHON (Jan 2018 - Sep 2018)
- I was in charge of the competition flow design, data preparation, technical support, and so on.
- For the promotion purpose, I gave a talk about speech recognition at Microsoft Tech Hub and GAN at Taiwan R User Group
A kubernetes based application aims to link our content delivery system to the online readers according to their real time behaviors.
- I lead the system architecture design
- Handle concurrent traffic from over 5M users everyday
- Leverage google cloud services such as GKE, GAE, and Pub/Sub.
Deep learning is fascinating, I was a member of "Deep learning 101 Study Group" and learned a lot from there. However, in practical scenarios, it's surprising to see some fundamental algorithms can show us more insights.
- PySpark dataframe programming
- Recommendation algorithm design, improved and achieved the best performance at that time
- Various classification tasks
- User profile construction with NLP.
- Information retrieval based chat bot
I created some tools(e.g., airfly) to help us management our data more efficiently.
- Based on PySpark
- Auto DAG generator: automatically resolve and build the task dependencies for our data pipeline
- Metadata management.
- More easier to perform data analytics such as EDA, data mining, machine learning tasks, etc.
- Leverage Google Dataproc to handle large scale adhoc queries for business team.
- Provide daily user demographics, metrics and reports with datastudio.
- I was in charge of the competition flow design, data preparation, technical support, and so on.
- For the promotion purpose, I gave a talk about speech recognition at Microsoft Tech Hub and GAN at Taiwan R User Group
Former work experiences
Zuirens
Computer Vision Engineer, Sep 2016 - Sep 2017
- Software and hardware integration planning.
- Object detection algorithm development based on OpenCV and C++/Python.
- Application Implementation based on Qt framework.
- Media server deployment for live streaming service.
- Crawler implementation and management.
- Web development planning.
Acuratek
Embedded Application Engineer, May 2015 - Jan 2016
- POC Applications based on development platforms such as PIC32, nRF52xx, 8051, etc.
- Android development based on OTG application.
Mechtronic Integration Engineer, Sep 2014 - Sep 2015
- 3-axis servo control with X-Y linear guideway installation.
- Mechatronic system and software integration.
- Application based on C# programming.
CORMA
Interactive Mechatronic Engineer, Aug 2013 - Aug 2014
- Motors and sensors control based on Arduino.
Skills
Programming Languages
mainly Python for now (open-minded to other languages if needed)
Frameworks and Tools
PySpark, Docker, Google Cloud Services, Jupyter, Sanic, Fabric, scikit-learn, Tensorflow.
Others
Linux, Emacs
Side Projects
- airfly: a tool for auto generating Airflow dag file, 2021. [repo]
- gutt: a tool for auto generating unit test template, 2021. [repo]
- Spark CodeFight Hackathon, 2017. [repo]
- OpenCV project for pattern matching and object tracking, 2017 [repo]
- Conversation retrieval based chit-chat bot, 2017. [repo]
- Kaggle competitions, ICDM 2015: top 25%, BNP 2016: top 5%. [kaggle info]
Awards & Honors
- 2017 PyCon speaker, [slide]
- 2017 HackNTU, Mentor.
- 2016 PIXNET HACKATHON, "Best A.I. Cloze Award".
Activities
- Machine Learning Certification on Coursera, 2015.
- Deep learning 101 Study Group, study topic: RNN, 2017 - now.
- Spark Taiwan Study Group, 2016 - 2017.
Education
National Cheng Kung University, Taiwan
BS, Mechanical Engineering
Ryan Chao
[email protected] • 0978903016 • Taipei, Taiwan
Hi, I'm Ryan, my current research interests include natural language processing, data engineering, machine learning and data related applications, and these are also my daily duties.
Experience
PIXNET
Assistant Manager, Aug 2020 - Sep 2022
- Lead data team(Aug 2020 - now)
Lead and manage data team with 6 members, we are dedicated to deliver insights from data to the company, not only support decision-making for business but also provide tech solutions to our services and products. My contributions includes:
- Architecture and methodology review for data solutions and various data analytic tasks
- Translate abstract business problems into solvable engineering components
- Project planning and management
- Goal alignment
Advanced Algorithm Engineer, Oct 2017 - Aug 2020
- Data streaming system development for near real time user tagging (Jan 2020 - Jul 2020)
A kubernetes based application aims to link our content delivery system to the online readers according to their real time behaviors.
- I lead the system architecture design
- Handle concurrent traffic from over 5M users everyday
- Leverage google cloud services such as GKE, GAE, and Pub/Sub.
- General algorithm development in large scale (Oct 2017 - now)
Deep learning is fascinating, I was a member of "Deep learning 101 Study Group" and learned a lot from there. However, in practical scenarios, it's surprising to see some fundamental algorithms can show us more insights. - PySpark dataframe programming
- Recommendation algorithm design, improved and achieved the best performance at that time
- Various classification tasks
- User profile construction with NLP.
- Information retrieval based chat bot
- Data warehousing and ETL management (Feb 2019 - now)
I created some tools(e.g., airfly) to help us management our data more efficiently.
- Based on PySpark
- Auto DAG generator: automatically resolve and build the task dependencies for our data pipeline
- Metadata management.
- More easier to perform data analytics such as EDA, data mining, machine learning tasks, etc.
- BI platform development (April 2019 - Oct 2019)
- Leverage Google Dataproc to handle large scale adhoc queries for business team.
- Provide daily user demographics, metrics and reports with datastudio.
- Tech lead of our 5th PIXNET HACKATHON (Jan 2018 - Sep 2018)
- I was in charge of the competition flow design, data preparation, technical support, and so on.
- For the promotion purpose, I gave a talk about speech recognition at Microsoft Tech Hub and GAN at Taiwan R User Group
A kubernetes based application aims to link our content delivery system to the online readers according to their real time behaviors.
- I lead the system architecture design
- Handle concurrent traffic from over 5M users everyday
- Leverage google cloud services such as GKE, GAE, and Pub/Sub.
Deep learning is fascinating, I was a member of "Deep learning 101 Study Group" and learned a lot from there. However, in practical scenarios, it's surprising to see some fundamental algorithms can show us more insights.
- PySpark dataframe programming
- Recommendation algorithm design, improved and achieved the best performance at that time
- Various classification tasks
- User profile construction with NLP.
- Information retrieval based chat bot
I created some tools(e.g., airfly) to help us management our data more efficiently.
- Based on PySpark
- Auto DAG generator: automatically resolve and build the task dependencies for our data pipeline
- Metadata management.
- More easier to perform data analytics such as EDA, data mining, machine learning tasks, etc.
- Leverage Google Dataproc to handle large scale adhoc queries for business team.
- Provide daily user demographics, metrics and reports with datastudio.
- I was in charge of the competition flow design, data preparation, technical support, and so on.
- For the promotion purpose, I gave a talk about speech recognition at Microsoft Tech Hub and GAN at Taiwan R User Group
Former work experiences
Zuirens
Computer Vision Engineer, Sep 2016 - Sep 2017
- Software and hardware integration planning.
- Object detection algorithm development based on OpenCV and C++/Python.
- Application Implementation based on Qt framework.
- Media server deployment for live streaming service.
- Crawler implementation and management.
- Web development planning.
Acuratek
Embedded Application Engineer, May 2015 - Jan 2016
- POC Applications based on development platforms such as PIC32, nRF52xx, 8051, etc.
- Android development based on OTG application.
Mechtronic Integration Engineer, Sep 2014 - Sep 2015
- 3-axis servo control with X-Y linear guideway installation.
- Mechatronic system and software integration.
- Application based on C# programming.
CORMA
Interactive Mechatronic Engineer, Aug 2013 - Aug 2014
- Motors and sensors control based on Arduino.
Skills
Programming Languages
mainly Python for now (open-minded to other languages if needed)
Frameworks and Tools
PySpark, Docker, Google Cloud Services, Jupyter, Sanic, Fabric, scikit-learn, Tensorflow.
Others
Linux, Emacs
Side Projects
- airfly: a tool for auto generating Airflow dag file, 2021. [repo]
- gutt: a tool for auto generating unit test template, 2021. [repo]
- Spark CodeFight Hackathon, 2017. [repo]
- OpenCV project for pattern matching and object tracking, 2017 [repo]
- Conversation retrieval based chit-chat bot, 2017. [repo]
- Kaggle competitions, ICDM 2015: top 25%, BNP 2016: top 5%. [kaggle info]
Awards & Honors
- 2017 PyCon speaker, [slide]
- 2017 HackNTU, Mentor.
- 2016 PIXNET HACKATHON, "Best A.I. Cloze Award".
Activities
- Machine Learning Certification on Coursera, 2015.
- Deep learning 101 Study Group, study topic: RNN, 2017 - now.
- Spark Taiwan Study Group, 2016 - 2017.
Education
National Cheng Kung University, Taiwan
BS, Mechanical Engineering