Sidharth Gulati is a machine learning engineer and SDE II based in Mountain View with about 2 years of professional experience in ML and a longer track record across embedded and cloud teams. He has applied statistical signal-processing and deep learning methods in both startups (Percolata, Qeexo) and at scale platforms (AWS), working end-to-end from prototyping in Python/Matlab/R to deploying models with PyTorch and TensorFlow. His background in electrical engineering (UCLA MS, NSIT BE) and an early research stint at DRDO give him a strong foundation in statistical modelling and optimized estimators that he brings to production ML problems. Comfortable across the stack, he has hands-on experience in data science toolkits (pandas, scikit-learn, numpy) and practical deployment challenges from multi-wallet e-commerce systems to sensor-driven ML products. He maintains a public GitHub and academic site, signaling a blend of research curiosity and production focus.
2 years of coding experience
7 years of employment as a software developer
Summer School, Statistics, Electrical Enagineering, A, Summer School, Statistics, Electrical Enagineering, A at University of California, Berkeley
Bachelor’s Degree, Electronics and Communications Engineering, First Class With Distinction, Bachelor’s Degree, Electronics and Communications Engineering, First Class With Distinction at Netaji Subhas Institute of Technology
Master’s Degree, Electrical Engineering, 3.74, Master’s Degree, Electrical Engineering, 3.74 at University of California, Los Angeles
Amazon Q, CodeCatalyst, Local Lambda debug, SAM/CFN syntax, ECS Terminal, AWS resources
Contributions:1 review in 1 day
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