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上級
On
4〜6年
6〜10年
10〜15年
15年以上
India
Senior Software Engineer
1年以上
software firm. Experienced with PYTHON, DJANGO Familiar with JAVA, J2EE, REST and SOAP Strong with OOPS and RDBMS concept. Experience Collabera (Client: Dell R nd D), OctPresent Working with server performance test automation with Python. Mindlogicx, JanOct 2017 Worked with examination based web application with Python and Django Tripmidas, AprJan 2017 Worked with corporate travel management based web application with python, Django, Java, J2EE Axa Business Services, JanApr 2016 Process automation with python Educational Details Bsc Computer Science, University Institute of Technology, Kerala University (65%) Disclaimer I hereby declare that the information and facts furnished here are
面接の用意ができています
パートタイム / リモートワークに興味あり
6〜10年
university institute of technology
・
computer science
Mern Stack Developer @H-Card2019 ~ 2019
・
Senior Software Developer
3ヶ月以内
and implementing an automated website builder using expertise in the MERN (MongoDB, Express.js, React.js, Node.js) stack and Python , streamlining the website development process and improving efficiency. Contributed to the enhancement of the Sapiens Architecture by incorporating various AI and data analytics algorithms using Django , enabling advanced functionalities and insights within the system. Responsible for implementing presentation and business logic for a high-traffic software application serving 1.2 million users . SeptemberJuly 2021 Mysore, Karnataka Project Engineer Wipro Technologies Played a key role in designing the frontend interface for server management
就職中
・
就職希望
フルタイム / リモートワークに興味あり
4〜6年
oriental college of technology
・
Computer Science
Web Developer @Self employed2017 ~ 現在
・
Python Developer
6ヶ月以内
/ Summary A passionate web developer dedicated to crafting exceptional online experiences. With a background in Computer Application , I've spent 5 years honing my skills and working on a variety of web development projects. "Versatile Python Django cum Web Developer with a comprehensive skill set encompassing the Django web framework and expertise in front-end technologies. Experienced in full-stack web development, with a strong ability to create robust, user-friendly web applications. " Work Experience Web Developer • Self employed SeptemberPresent GST Accountant • RJ associate SeptemberJune 2022 Education AVODHA EDUTECH PVT LTD Python DjangoDe Paul Institute
就職中
フルタイム / リモートワークに興味あり
4〜6年
AVODHA EDUTECH PVT LTD
・
Python Django
Software Engineer @411 Locals2022 ~ 現在
・
Senior Software Engineer
6ヶ月以内
Yuvraj Hinger India || [email protected] Experienced Bitrix CRM Developer with a focus on customization, workflow optimization, and integration. Proficient in Lamp Stack, AWS Solutions. Work Experience Software Engineer • 411 Locals NovemberPresent Communication Enhancements - As part of company marketing strategies, I was responsible for designing and implementing complex marketing cadences including customer journey - onboarding, off-boarding, accounting workflows etc. I was also involved in cadences reporting applications, implement A/B test and contribute in optimization process for customer experiences. Payment Integration and Gateway - For company different services, I was involved in various SaaS
就職中
フルタイム / リモートワークに興味あり
4〜6年
Geetanjali Institute of Technical Studies, Udaipur
・
Computer Programming
Senior Software Engineer ( OS Development - Android, Linux Kernel ) @Esper2019 ~ 現在
・
Senior Android Engineer
6ヶ月以内
Android • SDK Development for iOS • Network Protocol Development using C, C++ • Low Level Debugging in C, C++ & Assembly AugustNovember 2017 Staff Software Engineer Enfini Technology Solutions Pvt. Ltd. Responsibilities • Android app development using Java • iOS app development using Swift • RESTful API development using Python Django • Frontend development using React, Redux and CSS FlexBox • Databse design using PostgreSQL and MySQL Skills Android Applications Development Android Frameworks Development Android Systems Development Software Architectural Design Java Kotlin Low Level Design High Level Design Data Structures and Algorithms Systems Design Technical Leadership Android SDK Android NDK JNI C
就職中
フルタイム / リモートワークに興味あり
6〜10年
Chhattisgarh Swami Vivekanand Technical University, Bhilai
・
Computer Engineering
Sr. Laravel Developer @Nyusoft Solution LLP2021 ~ 2022
・
Senior React, Laravel, Django Full-Stack Web Developer
1年以内
就職中
フルタイム / リモートワークに興味あり
6〜10年
MARWADI EDUCATION FOUNDATION-FACULTY OF PG STUDIES AND RESEARCH IN ENGINEERING AND TECHNOLOGY-116
・
Computer EngineeringPast
App Developer @Ekata Pool Companion2022 ~ 2023
・
Front-End / Back-End / Full Stack Web Developer
1年以内
無職
フルタイム / リモートワークのみ
6〜10年
Backend Developer、IoT、DevOps、 Tech Lead、PM
1年以内
. Developed an energy-efficient Smart Metering System for a client based in the United Kingdom. It would add immense value to his business. Coded an efficient sustainable API server for web applications. Mentored freshers and enabled them to deliver industry-ready solutions. Technology Stack : Angular, Django, PyQt5, Python, MySQL, GIT, MQTT, WebSocket, Raspberry Pi, Zigbee Devices, Electrical Loads Software Engineer • IBS Software JunFeb 2020 | Location: Cochin, India Highlights Project: IFlight Crew-Neo Developed a critical solution for Leave Allocation for British Airways which is scheduled to go live by 2021 Implemented an optimized solution for
就職中
フルタイム / リモートワークに興味あり
4〜6年
フルタイム / リモートワークに興味あり
4〜6年
Maharshi Dayanand Saraswati University
・
BCASenior Software Engineer @Hypersonix2021 ~ 現在
・
Project Engineer HP
1年以上
Adding NPI New Product Identification support for the new products ➢ Design and development of print and scan features ➢ Have worked on scan UI using PyQt ➢ Build activities using Jenkins server ➢ Unit Testing and Maintenance ➢ Have worked on Print Contract feature Project2 : Launchpad Customer Site Using Django Duration : 2019 June to 2021 Jan Framework Used : Django EducationGTU Computer Engineering/10 (CGPASecondary Education Board H.S.C% (OverallSecondary Education Board Secondary Education Board% Skills Excellent Communication Written Skills Application Life Cycle Management Django Framework FastAPI Flask python programming SNOWFLAKE Pandas Numpy Docker Microservices MySQL
フルタイム / リモートワークに興味あり
4〜6年
GTU
・
Computer Engineering 最も簡単で効果的な採用プラン
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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.
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Professions
Data Engineer
Fields of Employment
ソフトウェア
職務経験
2〜4年
Management
スキル
言語
English
・
ビジネスレベル
Marathi
・
ネイティブまたはバイリンガル
Hindi
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Job search preferences
希望のポジション
Machine Learning Engineer
求人タイプ
フルタイム
希望の勤務地
リモートワーク
リモートワークに興味あり
Freelance
学歴
学校
Pune Institute of Computer Technology, Pune
専攻
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