Muhammad Nizamani is an AI programmer and machine learning engineer with 7 years of experience building backend systems and production-ready ML models. He combines FastAPI and Django expertise with hands-on TensorFlow and PyTorch work to deploy image, NLP, and recommendation solutions, and has practical experience in authentication, REST APIs, and database integrations. An active open-source contributor to the Ivy project, he implemented and tested core tensor math functions (asin, sqrt, log, exp, etc.), showing attention to numerical correctness that benefits cross-framework model portability. Based in Sindh, Pakistan, he brings a systems-engineering background from Mehran University and a track record of turning experimental models into reliable services at companies like AIFist and AIME. Colleagues describe him as a problem-solver who thrives on complex, end-to-end engineering challenges and incremental improvements to ML tooling.
7 years of coding experience
1 year of employment as a software developer
Bachelor of Engineering - BE Computer system Engineering, Bachelor of Engineering - BE Computer system Engineering at Mehran University of Engineering and Technology
Contributions:26 reviews, 66 PRs, 250 comments in 9 months
Contributions summary:Muhammad's contributions primarily focused on adding and integrating new machine learning functionality within the Ivy framework. They implemented the `asin` function within the paddle.tensor module, and subsequently added tests for its functionality. Further development includes adding, and testing other core math function like sqrt, asinh, log, exp, cos, erf, tanh, and others.
Contributions:809 pushes, 75 branches, 1 comment in 4 months
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