Shweta J
Software Developer - AI at Siemens EDA (Siemens Digital Industries Software)
Saskatoon, Saskatchewan, Canada
Summary
👤
Senior🎓
Top SchoolShweta J is a Software Developer - AI based in Saskatoon with a decade of experience building scalable applications and data-driven solutions across industry and academia. She combines strong software engineering practices—TDD, agile delivery, Java/Spring and end-to-end web development—from roles at Thoughtworks and Siemens with hands-on data analysis and dashboarding experience at Red Wireless. Her research background in graph neural networks (co-author on a CIKM paper) and open-source contributions to the widely used PyTorch Geometric project (type hints, pooling improvements, explainability metrics) reflect a rare blend of ML research rigor and production engineering. Known for mentoring and cross-functional collaboration, she translates complex datasets into actionable business insights and optimized reporting pipelines. With top academic performance (MSc 4.18/4.30) and a track record of improving code quality and model analysis, she’s positioned to bridge research-grade ML techniques and reliable production software.
10 years of coding experience
6 years of employment as a software developer
Computer Science, 93.2%, Computer Science, 93.2% at Vidyodaya School - IndiaEmirates National School, Sharjah9.8/10.0, 9.8/10.0 at Mar Thoma Public School - IndiaMaster of Science - MS, Computer Science, 4.18/4.30, Master of Science - MS, Computer Science, 4.18/4.30 at Ontario Tech UniversityBachelor of Technology - BTech, Computer Science, 3.9/4.0, Bachelor of Technology - BTech, Computer Science, 3.9/4.0 at Cochin University of Science and Technology
English, Hindi, Malayalam, Arabic
Github Skills (9)
pytorch10
machine-learning10
pytorch-geometric10
deep-learning10
graph-neural-network10
python10
type-checking9
type-inference9
typehinting9
Programming languages (3)
Github contributions (5)
pyg-team/pytorch_geometric
Oct 2022 - Dec 2022
Graph Neural Network Library for PyTorch
Role in this project:
ML Engineer
ML EngineerContributions:5 reviews, 7 commits, 11 PRs in 2 months
Contributions summary:Shweta's contributions primarily involve adding type hints and making code coverage improvements related to the PyTorch Geometric library. These changes involve enhancing the functionality of pooling layers and core components such as `avg_pool`, `max_pool`, `EdgePooling`, `SAGPooling`, and `dense_mincut_pool`. Additionally, the user contributed to adding accuracy metrics for evaluating explainability results with ground truth, demonstrating a focus on model analysis.
pytorchgraph-convolutional-networksgeometric-deep-learningdeep-learningneural-graph
shhs29/TodoApp
Nov 2019 - May 2022
A simple implementation of a TODO App
Contributions:17 PRs, 28 pushes, 18 branches in 2 years 6 months
reacttodo-appjavascriptnodejstypescript
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