Yeshwanth Nagaraj is a Principal Machine Learning Engineer with a decade of experience building production ML and software systems across Microsoft, Philips, Morgan Stanley and GE Healthcare. He combines deep engineering chops in Python, C++, Java and frontend frameworks with hands-on ownership of identity/access tooling, CI/CD automation and data pipelines that improved reliability and reduced operational issues for thousands of users. At Morgan Stanley he delivered cross-geography batch pipelines and developer APIs that eliminated recurring support complaints and accelerated migrations, and at GE he bridged MRI host software with deep-learning reconstruction efforts. A pragmatic QA contributor to the widely used sympy project, he has fixed subtle array-indexing bugs—illustrating attention to correctness in numerical code. Based in Karnataka, India, he pairs IIT Madras training in algorithms with a proven track record of turning complex, regulated domain requirements into resilient, measurable systems.
10 years of coding experience
10 years of employment as a software developer
Indian Institute of Technology Madras
Bachelor of Engineering (BE), Electronics and Communication Engineering, Bachelor of Engineering (BE), Electronics and Communication Engineering at Visvesvaraya Technological University
Contributions:6 commits, 2 PRs, 8 comments in 1 month
Contributions summary:Yeshwanth primarily focused on testing the `sympy` library's array functionality, specifically addressing inconsistencies with negative indexing. Their contributions involved writing and modifying test cases to verify the correct behavior of array indexing with negative values. They added assertions to ensure the expected output, revealing and fixing bugs in the process, thereby improving the reliability of array operations within `sympy`. The commits also include removing tabs to fix potential build failures.
Contributions:9 pushes, 1 branch in 5 years 6 months
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Yeshwanth Nagaraj - Principal Machine Learning Engineer at Microsoft