About

Pradnyesh Vineet Joshi is an Applied Scientist with a strong background in building end-to-end solutions using deep learning, NLP, machine learning, and recommender systems. With 3.86 years of relevant experience, he has a proven track record of developing and deploying models on cloud platforms and creating backend services for model serving. Currently working as an Applied Scientist II at Microsoft, Pradnyesh is a part of the Azure Gaming Services Team in Xbox. He is responsible for developing recommendations for the gaming industry and contributes to maintaining https://github.com/microsoft/recommenders. Prior to his current role, Pradnyesh worked as a Machine Learning Engineer at Houzz and Jewel ML. At Jewel ML, he developed an end-to-end content-based recommendation system for an e-commerce website. He trained a deep network using triplet sampling loss to learn fine-grained item embeddings and built a personalized recommender system using Deep Factorization Machines (DeepFM) and Bayesian Personalized Ranking (BPR) algorithm. He also automated recommendation updates using cloud scheduler and cloud functions on Google Cloud Platform. Additionally, he developed a backend service using NodeJS/Typescript to serve model recommendations and deployed it on GCP. Pradnyesh holds a Master of Science in Statistics from the University of Illinois at Urbana-Champaign and a Bachelor of Technology in Information Technology from the National Institute of Technology Karnataka. His tech stack includes Research Scientist, ML, Deep Learning, NLP, Backend, Azure, Typescript, Recommendation system, NodeJS, GCP, and UI. Overall, Pradnyesh is a highly skilled Applied Scientist with a passion for building innovative solutions using cutting-edge technologies. He is a quick learner, a team player, and has a strong work ethic.