Mohit Tare

Mohit Tare

Lead Ml Engineer Conversational AI @ RingCentral

About Mohit Tare

Mohit Tare is a Lead ML Engineer specializing in Conversational AI at RingCentral in Bengaluru, India, where he has worked since 2022. He has extensive experience in machine learning, having previously held positions at InfoCepts, Citi, Dell Technologies, and airtel X Labs.

Work at RingCentral

Mohit Tare serves as the Lead ML Engineer in the Conversational AI division at RingCentral, a position he has held since 2022. Based in Bengaluru, Karnataka, India, he focuses on various projects related to voice activity detection and language identification. Tare leads initiatives aimed at enhancing multilingual speech-to-text capabilities, particularly for accented and code-mixed languages. His work also includes contributions to automated agent coaching and feedback systems utilizing Generative AI.

Previous Experience in Machine Learning

Prior to his current role, Mohit Tare accumulated extensive experience in machine learning across several organizations. He worked at airtel X Labs as a Senior Lead Engineer in Machine Learning from 2019 to 2022. Before that, he was a Machine Learning Engineer at Dell Technologies from 2018 to 2019 and at Citi from 2017 to 2018. His earlier experience includes a role as an Associate Consultant in the Advanced Analytics Vertical at InfoCepts from 2014 to 2017.

Education and Expertise

Mohit Tare earned his Bachelor of Engineering (B.E.) degree in Computer Technology/Computer Systems Technology from Yeshwantrao Chavan College of Engineering (YCCE) between 2010 and 2014. His educational background provides a solid foundation for his expertise in machine learning and artificial intelligence, particularly in the context of conversational AI and speech analytics.

Research and Development Initiatives

In his current role at RingCentral, Mohit Tare conducts experiments in contextual biasing for speech analytics. He is also involved in speaker diarization and identification initiatives, which are critical for improving the accuracy and efficiency of conversational AI systems. His work contributes to the advancement of NLU and Generative AI initiatives within the organization.

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