Faramarz Munshi is a data scientist with 8 years of experience building production-grade ML systems, currently implementing real-time, large-scale anomaly detection at Apple that monitors hundreds of thousands of data points per minute with sub-5-minute end-to-end latency. He specializes in deep learning for NLP and time series, has contributed to GluonNLP and the D2L book, and has a UC Irvine master’s in computer science. Comfortable spanning full-stack engineering to research, he has led internal innovations that turned hack-week prototypes into product features and presented work to senior leadership. Multilingual and internationally educated, he pairs applied research experience from AWS, Pepperdata, and Yahoo with practical deployment skills across Spark, TensorFlow, and cloud infrastructures.
8 years of coding experience
2 years of employment as a software developer
University of California, Irvine
Bachelor of Science (B.S.), International Management in China, Bachelor of Science (B.S.), International Management in China at School of Oriental and African Studies, U. of London
The Chinese University of Hong Kong (CUHK)
Bachelor's degree - Year Abroad Requirement, 中文和经济学, -, Bachelor's degree - Year Abroad Requirement, 中文和经济学, - at 北京师范大学珠海分校
High School Diploma, High School Diploma at Henry M. Gunn High School
English, Chinese, modern standard arabic, Hindi, Gujarati, Urdu
Contributions:12 PRs, 25 pushes, 3 branches in 10 days
nlpstarcraftldasquadmachine-learning
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