Summary
Mayur Jadhav is a software engineer with a decade of experience building high-performance systems across graphics, virtualization, and cloud platforms, currently at AWS after senior engineering roles at Rivian and VMware. He specializes in C++ systems programming—optimizing Microsoft Teams in VDI using WebRTC and leading Linux client integrations like ringer, screen-sharing, and volume control—while also shipping test tooling that simulates Teams audio redirection without a VDI. Previously at Intel he worked on WindowsML/DirectML driver functionality and GPU kernel integration for deep learning inference, and at NVIDIA he built driver-quality and automation tooling that surfaced regressions and coverage gaps. His academic background includes an MS in Computer Science from Stony Brook with systems and storage research and hands-on kernel/OS and CPU design projects, plus Andrew Ng’s deep learning specialization. Comfortable across low-level GPU/kernel work and higher-level automation/testing, he combines performance tuning with practical tooling that reduces validation overhead. Based in the Bay Area, he brings a rare mix of graphics, ML inference, virtualization, and test-framework expertise to solve complex production problems.
10 years of coding experience
9 years of employment as a software developer
Bachelor of Engineering (B.E.) Computer Engineering, Bachelor of Engineering (B.E.) Computer Engineering at Sinhgad
SSC, SSC at Saint Lawrence High School, Aurangabad
Master of Science (M.S.) Computer Science, Master of Science (M.S.) Computer Science at Stony Brook University