About

Nilesh Khade is an Applied Data Scientist II at Microsoft with over 5 years of experience in the field of Machine Learning and Deep Learning. He holds a BTech(Hons.) and MTech from IIT Kharagpur in Computer Science and Engineering, and an MS in CS with ML specialization from UMass CS Amherst. His expertise lies in Software Development, Machine Learning, Deep Learning, and Database Management Systems. Currently, Nilesh works as a Data & Applied Scientist Intern at Microsoft's Azure Front Door CDN, where he has built a Neural Network-based Mult-CDN solution to provide ideal bandwidth distribution across multiple CDN providers. He has also modelled delayed metrics data as a time-series with LSTM and leveraged Azure ML services for model deployment. Nilesh has delivered an end-to-end application and hosted website for internal stakeholders to get live results and published the REST API to facilitate the consumption of results by downstream routing services. In his past roles, Nilesh has worked as a Software Engineer at qplum, where he was responsible for developing components and maintaining the trading pipeline based on Python using Airflow as the workflow management platform. He also worked on the development of a vectorized back-test framework to perform simulation for historical data in a faster and efficient manner. Nilesh has also worked as a Software Engineer at Two Roads Tech. Nilesh's interests lie in working on understanding the behavior of Deep Learning Models and scalability of Machine Learning Models for large datasets. He has a strong technical background and has worked with technologies such as Research Scientist, ML, Data Scientist, Azure, Deep Learning, Software Engineer, Neural Networks, Apache Airflow, test, and Python. Overall, Nilesh has 5.87 years of relevant experience and is a skilled Applied Data Scientist and Machine Learning Engineer. He is passionate about using his skills to make an impact in the field of Machine Learning and Deep Learning.