Samunder Singh
Associate Data Scientist
Bengaluru, Karnataka, India
Summary
🤩
Rockstar🎓
Top SchoolSamunder Singh is an Associate Data Scientist based in Bengaluru with 5 years’ experience building production-grade computer vision systems and ML infrastructure. He has shipped multi-GPU, multi-host CV inference pipelines, integrated segmentation and OCR into real-time inspection workflows, and designed self-supervised auto-labeling and CLIP-based anomaly detection pipelines. An active open-source contributor to Ivy and multiple ML backends, he’s added nuanced tensor ops and activation functions across Paddle, JAX, TensorFlow and PyTorch to ease framework portability. His background blends applied research—delivering <2% error in rhino height estimation and 98% detection accuracy—with backend engineering (Django–MongoDB) for scalable ML products. Notably, he’s contributed tooling that helps convert ML code between frameworks, reflecting a knack for making research-ready models robust and interoperable in production.
5 years of coding experience
1 year of employment as a software developer
Bachelor of Technology - BTech, Electrical, Electronics and Communications Engineering, Bachelor of Technology - BTech, Electrical, Electronics and Communications Engineering at Tezpur UniversityHigh School Diploma, High School Diploma at S.B.M senior secondary school ,suratgarh , rajasthan
Hindi, English
Github Skills (11)
tensorrt10
ivy10
paddle10
machine-learning10
tensor10
tensorflow10
python10
operation10
back-end-development10
deep-learning9
unit-testing9
Programming languages (4)
Github contributions (5)
ivy-llc/ivy
Jun 2023 - Mar 2024
Convert Machine Learning Code Between Frameworks
Role in this project:
Backend Developer
Backend DeveloperContributions:38 reviews, 103 PRs, 32 pushes in 9 months
Contributions summary:Samunder's primary contributions involve implementing and testing new functionalities for the Ivy framework, specifically focusing on the Paddle backend. Their commits added support for various paddle tensor methods, including bitwise operations, division, logical operations, reciprocal, bitwise not, and various activation functions such as ELU, HardTanh, and TanhShrink. They also integrated and tested new functionalities within the experimental API and added tests to ensure the correct implementation of the newly added methods.
pythontensorflowframework-learningtemplatedata-science
samthakur587/ivy
Jun 2023 - Apr 2024
Unified AI
Contributions:465 pushes, 146 branches in 9 months
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