About

Arjun Jauhari is a Senior Machine Learning Engineer at Spotify with over 9 years of relevant experience in the field of Natural Language Processing (NLP). He completed his Master of Engineering in Electrical and Computer Engineering from Cornell University in 2016 and has since worked with top companies like Amazon and IBM. Arjun's primary interest lies in building scalable and production quality NLP systems utilizing state-of-the-art Machine Learning and Deep Learning algorithms. He has worked on several NLP projects, including chatbots, information retrieval, and text analyzers. Arjun brings a healthy mix of research and engineering experience, having filed three patents and published a paper in CVPR. At Amazon Web Services, Arjun was a Software Development Engineer II in the AWS Deep Learning team and a member of the Amazon Kendra team since its inception until launch. He designed and successfully deployed an automatic framework for training machine learning models, which is currently being used by multiple AWS ML services in production. He also developed an automatic model evaluation strategy to catch any regression in model accuracy early in the cycle before any customer gets impacted. Furthermore, he led an Accuracy Troubleshoot Team to boost the performance of an E2E Machine Learning system with multiple ML models, closing the gap between online and offline systems by improving the F1 score from 4.16 to 47.2 (1075%). Arjun secured 2nd place victory in an internal Amazon ML competition with an F1 score of 64.9%, where the challenge was to classify safe vs unsafe products based on text reviews and star ratings. At IBM, Arjun was promoted to lead a team of Machine Learning Engineers to develop advanced ML solutions for NLP problems. He has a strong tech stack that includes ML, AWS, NLP, Deep Learning, Information Retrieval, and software engineering. Arjun's expertise in NLP and ML, coupled with his strong research and engineering background, makes him a valuable asset to any organization looking to build scalable and production quality NLP systems.