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On
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
India
Senior Software Engineer
超過一年
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
正在积极求职中
兼职 / 对远端工作有兴趣
6 到 10 年
university institute of technology
・
computer science
Mern Stack Developer @H-Card2019 ~ 2019
・
Senior Software Developer
三個月內
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
就职中
・
目前会考虑了解新的机会
全职 / 对远端工作有兴趣
4 到 6 年
oriental college of technology
・
Computer Science
Web Developer @Self employed2017 ~ 现在
・
Python Developer
半年內
/ 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
就职中
全职 / 对远端工作有兴趣
4 到 6 年
AVODHA EDUTECH PVT LTD
・
Python Django
Software Engineer @411 Locals2022 ~ 现在
・
Senior Software Engineer
半年內
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
就职中
全职 / 对远端工作有兴趣
4 到 6 年
Geetanjali Institute of Technical Studies, Udaipur
・
Computer Programming
Senior Software Engineer ( OS Development - Android, Linux Kernel ) @Esper2019 ~ 现在
・
Senior Android Engineer
半年內
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
就职中
全职 / 对远端工作有兴趣
6 到 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
一年內
就职中
全职 / 对远端工作有兴趣
6 到 10 年
MARWADI EDUCATION FOUNDATION-FACULTY OF PG STUDIES AND RESEARCH IN ENGINEERING AND TECHNOLOGY-116
・
Computer Engineering曾任
App Developer @Ekata Pool Companion2022 ~ 2023
・
Front-End / Back-End / Full Stack Web Developer
一年內
待业中
全职 / 我只想远端工作
6 到 10 年
Backend Developer、IoT、DevOps、 Tech Lead、PM
一年內
. 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
就职中
全职 / 对远端工作有兴趣
4 到 6 年
全职 / 对远端工作有兴趣
4 到 6 年
Maharshi Dayanand Saraswati University
・
BCASenior Software Engineer @Hypersonix2021 ~ 现在
・
Project Engineer HP
超過一年
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
全职 / 对远端工作有兴趣
4 到 6 年
GTU
・
Computer Engineering 最轻量、快速的招募方案，数百家企业的选择
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Search a precise keyword combination
senior backend php
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UI designer -UX
职场能力评价定义
专业技能
该领域中具备哪些专业能力（例如熟悉 SEO 操作，且会使用相关工具）。
问题解决能力
能洞察、分析问题，并拟定方案有效解决问题。
变通能力
遇到突发事件能冷静应对，并随时调整专案、客户、技术的相对优先序。
沟通能力
有效传达个人想法，且愿意倾听他人意见并给予反馈。
时间管理能力
了解工作项目的优先顺序，有效运用时间，准时完成工作内容。
团队合作能力
具有向心力与团队责任感，愿意倾听他人意见并主动沟通协调。
领导力
专注于团队发展，有效引领团队采取行动，达成共同目标。
专业背景
目前状态
求职阶段
专业
数据工程师
产业
软件
工作年资
2 到 4 年
管理经历
技能
语言能力
English
・
专业
Marathi
・
母语或双语
Hindi
・
母语或双语
求职偏好
希望获得的职位
Machine Learning Engineer
预期工作模式
全职
期望的工作地点
远端工作意愿
对远端工作有兴趣
接案服务
学历
学校
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