Debayan Ghosh is a Senior Machine Learning Engineer based in the San Francisco Bay Area, blending deep expertise in ML with a strong background in software and firmware systems. With nine years of experience spanning enterprise firmware at Western Digital to production ML roles and internships at Apple and CMU, he builds robust, production-ready ML pipelines and models for real-world applications. His work ranges from self-supervised keyword spotting for Siri to financial data pipelines and radar signal classification, reflecting comfort across speech, signal processing, and large-data ML. A CMU MS student focusing on machine learning, systems, and large-scale datasets, he actively bridges research and engineering to deploy scalable solutions. At femtoAI he progressed from ML Engineer to Senior ML Engineer, signaling rapid impact in a startup environment. He combines systems-level thinking with research experience—often translating academic methods into operational products.
8 years of coding experience
7 years of employment as a software developer
Bachelor of Engineering (B.E.) Electrical Electronics and Communications Engineering, Bachelor of Engineering (B.E.) Electrical Electronics and Communications Engineering at PES University
CBSE : AISSCE ( Grade 12 ) Physics Chemistry Math Computer Science, CBSE : AISSCE ( Grade 12 ) Physics Chemistry Math Computer Science at National Public School, Koramangala
Master of Science - MS Electrical and Computer Engineering, Master of Science - MS Electrical and Computer Engineering at Carnegie Mellon University
This repo contains the .NET Core runtime, called CoreCLR, and the base library, called System.Private.Corelib (or mscorlib). It includes the garbage collector, JIT compiler, base .NET data types and many low-level classes. We welcome contributions.
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