About

Amey Agrawal is a highly experienced CS PhD student at Georgia Tech, specializing in Systems for Machine Learning. With over 8 years of relevant experience in the tech industry, Amey has worked with some of the biggest names in the field, including Microsoft Research, Qubole, and Birla Institute of Technology and Science, Pilani. Currently working as a Software Engineer at Microsoft, Amey has a deep understanding of ML, software engineering, and research, and is well-versed in a wide range of programming languages and technologies, including Python, Spark, Keras, NLP, Javascript, Tensorflow, Pytorch, CNN, Neural Networks, MongoDB, UI, Web, Jupyter, Scikit, Data Science, Deep Learning, Redis, Flask, Information Retrieval, Sentiment Analysis, Reinforcement Learning, Random Forest, Django, Perceptron, Data Engineering, Big Data, MySQL, Jenkins, and Backend. During his time at Qubole, Amey was a Member of the Technical Staff 2, where he worked on a range of projects, including Qubole MLflow, Managed RStudio Service, Logan, and Application Proxy. His contributions to these projects earned him an early promotion and a Spotlight award. At Birla Institute of Technology and Science, Pilani, Amey served as a Teaching Assistant for 'BITS F464 Machine Learning', where he developed course material in Python, tutored students, and graded tests. Amey's technical expertise, combined with his passion for research and innovation, make him an ideal candidate for summer internships. His LinkedIn headline, "CS PhD student at Georgia Tech working on Systems for ML | Formerly: Microsoft Research, BITS Pilani, Qubole | Looking for Summer Internships |" highlights his commitment to learning and growing in the field of Machine Learning. In his LinkedIn summary, Amey describes himself as "Systems of ML/ML for systems", further emphasizing his expertise in this area. Overall, Amey Agrawal is a highly skilled and experienced professional with a passion for technology and innovation. His technical knowledge, combined with his dedication to learning and growing, make him an ideal candidate for any organization looking to push the boundaries of Machine Learning and Systems.