Ansh Tyagi
Town of Brookhaven, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolAnsh Tyagi is a pragmatic software engineer with six years’ experience building high-impact backend systems and a current MSCS candidate at Stony Brook University. He has driven measurable product gains at Headout—automating vendor integrations, cutting onboarding from days to minutes, and launching offers and notification systems that boosted conversions and reduced costs. Comfortable across Spring Boot WebFlux, REST/GraphQL, and TDD, he’s delivered high test coverage and led platform initiatives as the sole backend developer for key programs. Ansh also contributes to open-source deep learning tooling in Kotlin, implementing layers and initializers that improve Keras interoperability—an unusual mix of ML engineering and production backend expertise. Based in Brookhaven, NY, he pairs startup velocity with academic rigor to turn complex requirements into production-ready, data-informed features.
6 years of coding experience
4 years of employment as a software developer
Bachelor of Technology - BTech, Information Technology, Bachelor of Technology - BTech, Information Technology at Indian Institute of Information Technology(IIIT), SonepatClass XII, PCM, Class XII, PCM at Modern Vidya Niketan Sr. Sec. SchoolMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at Stony Brook University
Github Skills (7)
kotlin10
keras10
machine-learning10
deep-learning10
tensorflow10
unit-testing8
gpu8
Programming languages (14)
Github contributions (5)
Kotlin/kotlindl
Jun 2021 - Dec 2021
High-level Deep Learning Framework written in Kotlin and inspired by Keras
Role in this project:
ML Engineer
ML EngineerContributions:6 reviews, 9 commits, 11 PRs in 6 months
Contributions summary:Ansh primarily contributed to the development of deep learning layers and related infrastructure within the Kotlin Deep Learning project. Their work focused on implementing new layers such as GlobalAvgPool1D, MaxPool3D, and Permute, and also added functionalities like the Orthogonal initializer. The commits include unit tests and integration with the Keras model loading/saving functionality, demonstrating a focus on model building and interoperability.
gpudeep-learninghigh-levelmachine-learningkotlin
dsciiitsonepat/dsc-iiits
Jul 2021 - Aug 2021
Official Website of Google Developer Student Club IIIT Sonepat.
Contributions:4 reviews, 48 commits, 19 PRs in 1 month
student-clubiiitdeveloper-student-clubgoogle-developer-student-club
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