Summary
Harry Singh is a Senior Machine Learning Engineer with 11 years of experience building production-grade ML and distributed systems, currently applying his expertise at Netflix after roles at Apple and Cruise. A UC Berkeley MEng in EECS (Machine Learning), he combines deep learning (CNNs, RNNs, Transformers) and classical methods (SVM, convex optimization) with systems skills in C++ and Python to ship scalable, cloud-deployed solutions on AWS/GCP and containerized pipelines. His background in embedded and automotive systems (NIO, Cruise, self-driving projects) gives him an uncommon edge in deploying ML where reliability, remote diagnostics, and low-level integration matter. Notable achievements include creating a python-based remote firmware testing platform that saved thousands of man-hours and improving fleet deployment rates via targeted root-cause analysis. He balances research-caliber ML coursework and tools with practical engineering—building debugging tools, simulators, and autonomous vehicle hardware—making him adept at taking models from prototype to resilient production. Based in New York, he brings a cross-disciplinary perspective that bridges vehicle systems, cloud infrastructure, and applied ML.
11 years of coding experience
10 years of employment as a software developer
Master of Engineering - MEng Electrical Engineering and Computer Science - Machine Learning, Master of Engineering - MEng Electrical Engineering and Computer Science - Machine Learning at University of California, Berkeley
Bachelor of Science (BSc) in Engineering Mechanical Engineering Co-op, Bachelor of Science (BSc) in Engineering Mechanical Engineering Co-op at University of Alberta
Self-Driving Car ND, Self-Driving Car ND at Udacity
High School Diploma, High School Diploma at Strathcona High School
English, French, Hindi