Principal Engineer - Machine Learning at Marvell Technology
Toronto, Ontario, Canada
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Summary
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Ranjeeth Siddakatte is a Principal Engineer in Machine Learning based in Toronto with eight years of industry and research experience bridging signal processing, sensor fusion, and deep learning for navigation and autonomous systems. He holds a PhD focused on signal processing for navigation and has delivered measurable gains—such as 60% improvements in multi-frequency GNSS combining and 5–8 dB SNR boosts from novel tracking methods—applied to weak GNSS and indoor positioning. At Marvell and prior research roles he has moved algorithms from prototype to real-time embedded implementations, combining expertise in ANN/CNN training with low-latency DSP, FPGA and embedded software design. Comfortable across the stack, he develops and debugs neural nets in modern frameworks while also designing hardware-aware calibration and sensor fusion approaches for IMU and GNSS suites. Colleagues rely on him for turning rigorous academic ideas into production-ready, resource-constrained solutions for intelligent sensing.
8 years of coding experience
13 years of employment as a software developer
Bachelor of Engineering (B.Eng) Electronics and Communication, Bachelor of Engineering (B.Eng) Electronics and Communication at Visvesvaraya Technological University
Ph.D. in Engineering specialization: Signal processing for navigation and localization, Ph.D. in Engineering specialization: Signal processing for navigation and localization at University of Calgary
Contributions:14 commits, 13 pushes, 1 branch in 1 day
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Ranjeeth Siddakatte - Principal Engineer - Machine Learning at Marvell Technology