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4-6 years
6-10 years
10-15 years
More than 15 years
Past
後端工程師 & DevOps @創業家兄弟Kuobrothers Corp.2022 ~ 2024
・
Senior Backend Engineer | DevOps | SRE
Within one month
Unemployed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
National Taipei University of Technology
・
資工系
Past
Marketing Manager @幫你優股份有限公司 BoniO Inc. / 閱讀優有限公司 TaaO Company Limited2021 ~ Present
・
Marketing Manager
Within one month
李佳謙 CHIEN LI Marketing Manager / BoniO Inc. Marketing Strategy ｜ Customer Growth 負責品牌行銷，規劃產品銷售策略，推動品牌會員成長 熟悉市場、訂閱經濟、平台營運 以終為始策略型思考，帶領團隊有效達到營運目標 工作專長 用戶、營運成長數據指標分析 Operating Data Management ● 產品市場規模及用戶調
Unemployed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
淡江大學
・
英文學系
Past
Sr. Frontend Engineer @旭捷資訊有限公司2022 ~ 2023
・
前端工程師、資深前端工程師
Within one month
蔡卓霖 JavaScript | React 曾經是一名5年經驗的遊戲設計師， 現在是一名擁有4年開發經驗的資深前端工程師。 [email protected] 工作經驗 旭捷資訊 - Sr. Frontend Engineer | 2022/03 ~ 2023/10 ・ 1 yr 8 mos 個人金融服務產品 - 前端開發 ・使用 React, Redux Toolkit, TypeScript, Ant Design 和 Vite，從0到1開發產品與 後
Unemployed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
大仁科技大學
・
應用英文Unemployed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
暨南大學
・
電機工程
Past
UX/UI 設計師 @網際威信股份有限公司2023 ~ Present
・
UX/UI Designer
Within one month
張華容 產品設計師 [email protected] Taipei , Taiwan Hi！我是Chloe，專注於 用戶研究 與 使用者介面設計 及規劃 Design System 。 1年UIUX設計經驗，為銀行端功能優化成功提升 5%的使用率 。 3年網頁設計經驗，曾經為知名品牌Web設計 10+ 個案例 ，並成功讓網站 提升流量 15% 。 擅長良
Unemployed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
iSpan資展國際
・
前端工程師就業養成班
行銷副理 / KOL Radar 行銷科技事業部 @愛卡拉互動媒體股份有限公司2021 ~ Present
・
品牌專案企劃、網路行銷企劃、數位行銷企劃
Within one month
林孟嫻 (Naomi Lin) 超過 5 年整合行銷與專案策略經驗 ，善於跨部門溝通、協作與專案管理，以邏輯和創意超越一切挑戰。 Contact: [email protected] 【專業能力】 英語能力： 多益 955 分，曾任台大英語辯論賽裁判 產品與市場數據分析： GA4, Ahrefs, SimilarWeb, Hotjar, Google Looker Studio 圖表串接與分析 行銷
Employed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
臺北市立大學
・
英語教學系
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、Ai Application Engineer,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 Yuan Ze University
・
工業工程與管理學系所
Past
資深前端工程師 @辰凝有限公司2022 ~ 2023
・
前端工程師 Front-End Developer
Within one month
Sosuke Guo 專職於網頁前端工程師近五年，擅於從0開始打造產品，有用Vue + Golang + Python自己打造產品的經驗。 前端工程師 Front-End Developer 作品 - SocialPicMaker.com 製作精美Twtter card 的小工具網站 只要兩個步驟，輸入網址、點擊下載，即可完成 可以選擇黑白兩種介面佈局以及多種
Unemployed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
Algorithm Research & Development @適着三維科技股份有限公司 TG3D Studio Inc.2021 ~ Present
・
Software Engineer
Within one month
Patrick Hsu AI Research & Development As a seasoned AI engineer with six years of experience, I specialize in computer vision, 3D body model reconstruction, generative AI, and possessing some knowledge in natural language processing (NLP). | New Taipei City, [email protected] Work Experience (6 years) Algorithm Research & Design• TG3D Studio MayPresent A skilled engineer specialized in computer vision and generative AI with experience in developing and training AI models for digital fashion applications. Body AI: Virtual Try On Integrated cutting-edge technologies such as Stable Diffusion, ControlNet, and Prompt Engineering to create a sophisticated system for
Employed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
國立台灣大學
・
生物產業機電工程所Past
前端工程師 @科智企業股份有限公司2018 ~ 2023
・
資深前端工程師, Sr. Frontend Engineer
Within one month
Unemployed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
國立交通大學 National Chiao Tung University
・
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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
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Leadership
Ability to coach, guide, and inspire a team to achieve a shared goal or outcome effectively.
Within three months
Software Engineer
Jash Data Sciences
・
2020 ~ Present
Professional Background
Current status
Job Search Progress
Professions
Data Engineer
Fields of Employment
Software
Work experience
2-4 years
Management
Skills
Languages
English
・
Professional
Marathi
・
Native or Bilingual
Hindi
・
Native or Bilingual
Job search preferences
Positions
Machine Learning Engineer
Job types
Full-time
Locations
Remote
Interested in working remotely
Freelance
Educations
School
Pune Institute of Computer Technology, Pune
Major
Electronics and Telecommunication
Shishir Joshi
Full Stack Data Scientist and self taught Machine Learning enthusiast with experience of CV, NLP, Deep Learning and backend development.
Pune IN
[email protected]
Ph. : +91 8554067867 | +91 9405181761
Skills
Machine Learning
Transformers (BERT, DistillBERT),
LSTMs, CNNs, SVMs, KNN, Decision Trees,
ULMFiT,
Transfer Learning, Deep Learning, Computer Vision,
APIs / Libraries
OpenCV, Tensorflow, Keras, PyTorch, Fast.ai, Huggingface,
Scikit-Learn, Pandas,
PySpark.
Development
Python, shell scripting, Java, SQL/PL-SQL, GIT, Django, Flask
AWS [ EC2, S3, SQS, RDS, Sagemaker ]
Work Experience
Data Scientist,
GlobalFoundries | Mar 2021 ~ Present
: Predictive Maintenance Model of Semiconductor Etching Tools
- Created multiple POCs for predictive maintenance of semiconductor mfg. tools based on Remaining Useful Life using existing tool sensors and yield data for the Singapore Facility.
- XGBoost Regressor and Autoregressive LSTM models were developed for the same in AWS Sagemaker.
- Deployed models on premises in shadow mode for validation on live data.
: Probability of Failure analysis/ model on Etching Tools
- Built Probability of Failure model using test wafer particle counts to predict tool's internal state.
- Two part model is made of Wafer Particle (defect) Count Regressor (Linear Reg., RandomForest Reg., XGBoost Regressor were used for POCs) and Thresholded CDF of Negative Binomial distribution.
- Used Maximum Likelihood Estimation to model tool state based on multiple internal sensors, semiconductor recipe information and control limit thresholds.
- MLE model used with Threshold CDF framework shows promising results in terms of extending tool uptime and predicting possible failures based on trends in defect measurement.
Data Scientist,
Jash Data Sciences | Feb 2020 ~ Feb 2021
: Document Similarity Semantic Search
- Researched, created and served document level semantic similarity search engine for an AI based hiring tech startup.
- Compared the performance of LSTM Seq2Seq based Autoencoder for language modeling task with DistilBERT model on custom evaluation metric based on semantic similarity.
- Created complete backend API to serve the fine tuned DistilBERT model via Flask and Highly optimized document embedding.
- Implemented Approximate Nearest Neighbor search using graph based HNSW clustering for near real time retrieval.
: Insurance Email Classification and document NER
- Created word embedding and keyword extraction based email classification model (Test Set F1 score: 0.85).
- My model out performed ULMFiT model fine tuned for email classification on same dataset (ULMFiT Test Set F1 score: 0.72).
- Worked on implementing DistilBERT based NER pipeline using Huggingface Transformers.
: Inhovate - Analytics platform focused on the hospitality industry
- Automated complete ETL logic in Bash/Python.
- Worked on Backend API in Django and wrote custom query builders to dynamically compose and execute complex queries beyond the scope of Django's ORM.
- Created linux processes and cron jobs for ETL, web server with load balancing using HAProxy and Gunicorn.
Software Engineer,
Larsen and Toubro Infotech, | Sep 2018 ~ Dec 2019
- Development and extension of BRAINS core banking platform.
- Implemented source code management functionality in-house, saving $25k yearly in licensing costs to outsourced system
- Worked on pilot project for creation of defaulter classification using Gradient Boosted Decision Tree classifier in Scikit-Learn.
Projects (Computer Vision, NLP, etc.)
Click here for colab notebooks
Qualia
- https://github/qualia
- Online Real Time Semantic Search using Transformers and HNSW nearest neighbour search.
- Can be
fine tuned on specific datasets with custom tokenisation requirements.
- Uses Sentence Transformers
as embedding model and HNSWlib as approximate nearest neighbour search index based on cosine
similarity.
- The aim is to make it "Online" - to be able to add new documents in parallel with querying.
StackExchange Question tags extraction
- https://colab/stx
- Multilabel classification for tag extraction from Stackexchange questions.
- Used transfer learning to fine
tune ULMFiT Language model on dataset (83% language modeling accuracy),
- Used beautifulsoup4
(bs4) and regex to clean text.
- Created Multi-Label classifier using ULMFiT as embedding layer.
- Achieved >93% accuracy on tag prediction.
Machine Learning Based Automatic Fruit Grading and Classification
-
Machine Learning Based Automatic Fruit Grading and Classification:Funded by the University of Pune.
- Trained Inception V3 CNN model via transfer learning for detecting grade of fruits based on visual quality, skin texture, and pre-defined standards.
- Used OpenCV for image preprocessing (cropping, segmentation and feature extraction for comparison of classification on SVM) Achieved ~90% accuracy on test set.
MobileNet v2.0 Transfer Learning on the Caltech101 Dataset with TF2.0:
- Trained my custom CNN on the 101 categories of the Caltech101 dataset.
- Prepared a tf.Data input pipeline, and compared performance with transfer-trained MobileNetv2.0 model.
- My Model achieved ~98% accuracy while MobileNet achieved ~80%
Education
Savitribai Phule Pune University, Pune | 2015 ~ 2018
Bachelor of Engineering (B.E.) | Electronics and Telecommunication,
Graduated First Class with Distinction
from
Pune Institute of Computer Technology (PICT), Pune
Shishir Joshi
Full Stack Data Scientist and self taught Machine Learning enthusiast with experience of CV, NLP, Deep Learning and backend development.
Pune IN
[email protected]
Ph. : +91 8554067867 | +91 9405181761
Skills
Machine Learning
Transformers (BERT, DistillBERT),
LSTMs, CNNs, SVMs, KNN, Decision Trees,
ULMFiT,
Transfer Learning, Deep Learning, Computer Vision,
APIs / Libraries
OpenCV, Tensorflow, Keras, PyTorch, Fast.ai, Huggingface,
Scikit-Learn, Pandas,
PySpark.
Development
Python, shell scripting, Java, SQL/PL-SQL, GIT, Django, Flask
AWS [ EC2, S3, SQS, RDS, Sagemaker ]
Work Experience
Data Scientist,
GlobalFoundries | Mar 2021 ~ Present
: Predictive Maintenance Model of Semiconductor Etching Tools
- Created multiple POCs for predictive maintenance of semiconductor mfg. tools based on Remaining Useful Life using existing tool sensors and yield data for the Singapore Facility.
- XGBoost Regressor and Autoregressive LSTM models were developed for the same in AWS Sagemaker.
- Deployed models on premises in shadow mode for validation on live data.
: Probability of Failure analysis/ model on Etching Tools
- Built Probability of Failure model using test wafer particle counts to predict tool's internal state.
- Two part model is made of Wafer Particle (defect) Count Regressor (Linear Reg., RandomForest Reg., XGBoost Regressor were used for POCs) and Thresholded CDF of Negative Binomial distribution.
- Used Maximum Likelihood Estimation to model tool state based on multiple internal sensors, semiconductor recipe information and control limit thresholds.
- MLE model used with Threshold CDF framework shows promising results in terms of extending tool uptime and predicting possible failures based on trends in defect measurement.
Data Scientist,
Jash Data Sciences | Feb 2020 ~ Feb 2021
: Document Similarity Semantic Search
- Researched, created and served document level semantic similarity search engine for an AI based hiring tech startup.
- Compared the performance of LSTM Seq2Seq based Autoencoder for language modeling task with DistilBERT model on custom evaluation metric based on semantic similarity.
- Created complete backend API to serve the fine tuned DistilBERT model via Flask and Highly optimized document embedding.
- Implemented Approximate Nearest Neighbor search using graph based HNSW clustering for near real time retrieval.
: Insurance Email Classification and document NER
- Created word embedding and keyword extraction based email classification model (Test Set F1 score: 0.85).
- My model out performed ULMFiT model fine tuned for email classification on same dataset (ULMFiT Test Set F1 score: 0.72).
- Worked on implementing DistilBERT based NER pipeline using Huggingface Transformers.
: Inhovate - Analytics platform focused on the hospitality industry
- Automated complete ETL logic in Bash/Python.
- Worked on Backend API in Django and wrote custom query builders to dynamically compose and execute complex queries beyond the scope of Django's ORM.
- Created linux processes and cron jobs for ETL, web server with load balancing using HAProxy and Gunicorn.
Software Engineer,
Larsen and Toubro Infotech, | Sep 2018 ~ Dec 2019
- Development and extension of BRAINS core banking platform.
- Implemented source code management functionality in-house, saving $25k yearly in licensing costs to outsourced system
- Worked on pilot project for creation of defaulter classification using Gradient Boosted Decision Tree classifier in Scikit-Learn.
Projects (Computer Vision, NLP, etc.)
Click here for colab notebooks
Qualia
- https://github/qualia
- Online Real Time Semantic Search using Transformers and HNSW nearest neighbour search.
- Can be
fine tuned on specific datasets with custom tokenisation requirements.
- Uses Sentence Transformers
as embedding model and HNSWlib as approximate nearest neighbour search index based on cosine
similarity.
- The aim is to make it "Online" - to be able to add new documents in parallel with querying.
StackExchange Question tags extraction
- https://colab/stx
- Multilabel classification for tag extraction from Stackexchange questions.
- Used transfer learning to fine
tune ULMFiT Language model on dataset (83% language modeling accuracy),
- Used beautifulsoup4
(bs4) and regex to clean text.
- Created Multi-Label classifier using ULMFiT as embedding layer.
- Achieved >93% accuracy on tag prediction.
Machine Learning Based Automatic Fruit Grading and Classification
-
Machine Learning Based Automatic Fruit Grading and Classification:Funded by the University of Pune.
- Trained Inception V3 CNN model via transfer learning for detecting grade of fruits based on visual quality, skin texture, and pre-defined standards.
- Used OpenCV for image preprocessing (cropping, segmentation and feature extraction for comparison of classification on SVM) Achieved ~90% accuracy on test set.
MobileNet v2.0 Transfer Learning on the Caltech101 Dataset with TF2.0:
- Trained my custom CNN on the 101 categories of the Caltech101 dataset.
- Prepared a tf.Data input pipeline, and compared performance with transfer-trained MobileNetv2.0 model.
- My Model achieved ~98% accuracy while MobileNet achieved ~80%
Education
Savitribai Phule Pune University, Pune | 2015 ~ 2018
Bachelor of Engineering (B.E.) | Electronics and Telecommunication,
Graduated First Class with Distinction
from
Pune Institute of Computer Technology (PICT), Pune