About

Rishi Khetan is a Senior Data Scientist and Machine Learning Engineer with 6 years of experience in the field. He has a strong background in Deep Learning, Machine Learning, Big Data, Software Engineering, and Data Engineering. Rishi is passionate about incorporating the latest development trends and state of the art in Artificial Intelligence (AI) and Technology into his work. Rishi has extensive experience in researching capabilities such as Natural Language Processing (NLP), NLU, Computer Vision (CV), Audio, Speech (STT, etc.) using Deep Learning and Machine Learning. He has worked on projects driving business transformation through Advanced Analytics, Big Data, and Data Science. Rishi actively productionizes ML models with cloud deployment (AWS, Azure, GCP) at scale while incorporating best MLOps practices, with a focus on reducing model size, resource consumption, training, and inference times. In addition to being ambitious and driven to flourish, Rishi has an exalted regard for efficiency. He is critical in the prompt execution of his responsibilities and tasks to be decidedly productive with regard to his work performance. Rishi is well-suited for roles in Natural Language Processing (NLP), Computer Vision (CV), Audio, Speech, and has experience working as an Applied Scientist, Data Scientist, Machine Learning Engineer, Natural Language Processing Scientist/Engineer, Computer Vision Scientist/Engineer, Deep Learning Engineer/Researcher, Machine Learning Researcher/Scientist, Research Scientist/Engineer, Applied Research Engineer, AI Engineer/Scientist, Big Data Scientist, and ML Architect. Currently, Rishi is working as a Senior Machine Learning Engineer at Egnyte, where he is developing Document Intelligence capabilities such as PII detection, address extraction from unstructured text, etc. to enforce security and governance in Egnyte's product. He is also working on optimizing ML models in Egnyte app for edge deployment on iOS devices. Additionally, Rishi is supervising the full development of machine learning & deep learning projects, from design to deployment and maintenance. Prior to Egnyte, Rishi worked as a Senior Data Scientist at TomTom and as a Data Scientist II at HERE. At TomTom, he developed and productionized Distil BERT for POI categorization, served ~100M inferences a day on Azure, and conflated POIs from 500+ sources spanning ~240 countries. At HERE, Rishi researched Natural Language Processing (NLP) and Computer