Rishab Mallick
AI Product Engineer at metaintro
United Arab Emirates
Summary
🤩
Rockstar🎓
Top SchoolRishab Mallick is an AI Product Engineer with six years of experience building production-ready ML systems and developer-facing tooling from the UAE. He has shipped cross-framework integrations and runtime tooling—contributing backend improvements to the Ivy project that help convert ML code between frameworks—and has integrated Ivy across BentoML, Seldon, and other OSS deployment stacks. At Unify he led performance benchmarking, LLM provider routing, and transpiler work to make models and profilers framework-agnostic, and at Small Joys he tackled bias-mitigation and multimodal health pilots that outperformed commercial sentiment APIs on internal data. Comfortable across research and product, he has experience reducing biocuration time with NLP pipelines (published from a GSoC project) and deploying inference APIs on cloud and edge devices. He combines hands-on backend engineering, CI/CD on GCP, and product-facing demo leadership, with a knack for refactoring core systems to improve debuggability and maintainability.
6 years of coding experience
3 years of employment as a software developer
B. Tech, Computer Science, 8.84/10, B. Tech, Computer Science, 8.84/10 at St. Thomas' College of Engineering & Technology 122Kendriya Vidyalaya Sangathan
Github Skills (11)
ivy10
machine-learning10
python10
numpy9
documentation9
deeplearning-ai9
deep-learning9
pytorch8
converter8
tensorflow8
jax8
Programming languages (3)
Github contributions (5)
ivy-llc/ivy
Feb 2023 - Oct 2023
Convert Machine Learning Code Between Frameworks
Role in this project:
Backend Developer
Backend DeveloperContributions:83 reviews, 59 PRs, 36 pushes in 8 months
Contributions summary:Rishab primarily focused on enhancing and maintaining the core functionalities of the Ivy project. Their contributions included updating documentation, particularly docstrings, and refactoring code related to inplace updates and other core functionalities. The user also added and updated support for backend operations such as einops_repeat. Their work demonstrates an understanding of backend frameworks.
pythontensorflowframework-learningtemplatedata-science
rishabgit/Andrew-Ng-ML-solutions
Jun 2019 - Jul 2019
Solutions of the exercises of Andrew Ng's Machine Learning course available on Coursera (in Octave and Python).
Contributions:43 commits, 2 PRs, 41 pushes in 1 month
pythondata-scienceandrew-ngmachine-learning-coursemachine-learning
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