Shubham Gothale
About Shubham Gothale
Shubham Gothale is a Software AI Engineer at Gupshup in Bangalore Urban, Karnataka, India, with expertise in Natural Language Processing and Computer Vision. He has a strong background in machine learning, having worked at various technology companies and holds a Master of Technology from the Indian Institute of Technology, Kharagpur.
Work at Gupshup
Shubham Gothale has been employed as a Software AI Engineer at Gupshup since 2021. His role involves leveraging his expertise in artificial intelligence to develop solutions that enhance communication technologies. Gupshup operates in Bangalore Urban, Karnataka, a prominent center for technology and innovation in India. His contributions over the past three years have been significant in advancing the company's AI capabilities.
Education and Expertise
Shubham Gothale holds a Master of Technology (M.Tech) degree in Computer Science and Data Processing from the Indian Institute of Technology, Kharagpur, which he completed from 2017 to 2019. He also earned a Bachelor of Engineering (B.E.) in Electronics and Power Engineering from Nagpur University between 2011 and 2015. His educational background provides a strong foundation for his expertise in Natural Language Processing (NLP) and Computer Vision.
Professional Background
Shubham Gothale has a diverse professional background in the field of artificial intelligence and machine learning. Prior to his current role at Gupshup, he worked as an Associate Tech Lead - AI at Zycus for one year and as a Machine Learning Engineer at Quantiphi for eight months. His earlier experiences include positions as a Senior Computer Vision Developer at MLAI Technologies and a Research Intern at Tata Research Development and Design Centre (TRDDC). He also served as a Visiting Lecturer at the Government College of Engineering.
Technical Skills
Shubham Gothale possesses strong technical skills essential for AI and machine learning development. He is proficient in programming with Python, which is critical for developing machine learning models. Additionally, he has expertise in using frameworks and libraries such as Scikit-Learn, TensorFlow, and Keras, which are widely utilized in the industry for building and deploying machine learning applications.