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On
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
曾任
後端工程師 & DevOps @創業家兄弟Kuobrothers Corp.2022 ~ 2024
・
Senior Backend Engineer | DevOps | SRE
一個月內
黃季承 Backend Developer | DevOps [email protected]我從事 5 年的電商後端開發與 1 年的 DevOps 維運，並參與超過 4 年的 Scrum 敏捷開發。後端主要負責產品功能研發、後台系統開發與既有服務重構。曾參與生活市集即享券開發，負責與合作夥伴釐清事項、跟 PM 討論整合方式、設
待業中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
National Taipei University of Technology
・
資工系
曾任
Marketing Manager @幫你優股份有限公司 BoniO Inc. / 閱讀優有限公司 TaaO Company Limited2021 ~ 現在
・
Marketing Manager
一個月內
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
待業中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
淡江大學
・
英文學系
待業中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
暨南大學
・
電機工程就職中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
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 ~ 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、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
元智大學
・
工業工程與管理學系所
曾任
資深前端工程師 @辰凝有限公司2022 ~ 2023
・
前端工程師 Front-End Developer
一個月內
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 [email protected] 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
待業中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
Algorithm Research & Development @適着三維科技股份有限公司 TG3D Studio Inc.2021 ~ 現在
・
Software Engineer
一個月內
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
就職中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
國立台灣大學
・
生物產業機電工程所
曾任
Lead of Country Product Manager @Asus 華碩電腦股份有限公司2022 ~ 2023
・
Business Development / Product Manager / Product Marketing/ Strategy Manager
一個月內
Jimmy Lu (呂正彥) Senior Product Manager [Consumer Electronics Expatriate PM/Sales/BD] Entrepreneurship business development & management Leadership flexible & efficient international/cross-functional organizing Target-oriented project lead & SOP consolidation, product lifecycle management Begin with the end in mind Go-to-market execution Taipei, Taiwan < > London, UK https://www.linkedin.com/in/itsjimmy/ [email protected] Work experience Senior Product Manager [Consumer NB & Gaming ] • ASUSTeK Computer Indonesia JulDec 2023 | Jakarta, Indonesia Key responsibilities & Achievements - #business management #business development #team leading #cross-functional organizing
待業中
・
正在積極求職中
全職 / 對遠端工作有興趣
4 到 6 年
國立陽明交通大學(National Yang Ming Chiao Tung University)
・
Bachelor of management , Management of Transportation and Logistics
資深全端工程師 @誠諾工程技術股份有限公司2023 ~ 現在
・
Front-End / Back-End / Full Stack Web Developer
一個月內
張栢瑄 Ryan Po-Hsuan Chang 已有五年開發經驗，擅長使用Vue + TypeScript 和Laravel 來建構網頁系統，另外也有React 和Python 的開發經驗。喜歡挑戰新事務，不怕踩坑和重構，持續精進自己的技術。 Kaohsiung City, Taiwan https://ryanxuan930.github.io/ [email protected]技能 Frontend Nuxt (Vue 3) Next (React) Pinia TypeScript Tailwind CSS SCSS PrimeVue Next UI Backend
就職中
・
正在積極求職中
全職 / 我只想遠端工作
4 到 6 年
國立中山大學 National Sun Yat-Sen University
・
人文暨科技跨領域學士學位學程
運維工程師 DevOps @愛盛娛樂科技有限公司2019 ~ 現在
・
Java 軟體工程師
一個月內
楊晟 運維工程師 DevOps New Taipei City, Taiwan 喜歡尋找程式碼中更優雅的做法，熱衷找到更高效率、更優雅的解決方案。 喜歡尋找 Solution，討厭遷就 Workaround https://www.cakeresume.com/sam0324sam 工作經歷 運維工程師 DevOps • 愛盛娛樂科技有限公司 七月Present - 全遠端 - (作品集) 使用 Java Quarkus 開發 RESTful API 後
就職中
・
正在積極求職中
全職 / 我只想遠端工作
4 到 6 年
National Kaohsiung First University of Science and Technology
・
電腦與通訊工程系最輕量、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
求職階段
專業
數據工程師
產業
軟體
工作年資
2 到 4 年
管理經歷
技能
語言能力
English
・
專業
Marathi
・
母語或雙語
Hindi
・
母語或雙語
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
遠端工作意願
對遠端工作有興趣
接案服務
學歷
學校
Pune Institute of Computer Technology, Pune
主修科系
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