Vaibhav Kakodiya
About Vaibhav Kakodiya
Vaibhav Kakodiya is a Machine Learning Engineer currently working at Mindbody, where he develops AI/ML solutions for the payments team. He holds a Bachelor of Technology in Chemical Engineering from the Indian Institute of Technology, Bombay, and has experience in various technologies including Natural Language Processing and API design.
Work at Mindbody
Vaibhav Kakodiya currently serves as a Machine Learning Engineer at Mindbody, having joined the company in 2022. He works in Pune, Maharashtra, India, where he focuses on developing and deploying AI and machine learning solutions for the payments team. His role includes modernizing systems to improve efficiency and performance, exemplified by his work on the autopay system.
Previous Experience at Atyati Technologies
Before joining Mindbody, Vaibhav Kakodiya worked as a Software Engineer specializing in AI and machine learning at Atyati Technologies. He held this position for one year, from 2021 to 2022, in Bengaluru, Karnataka, India. His experience there contributed to his expertise in various technologies related to machine learning.
Education and Expertise
Vaibhav Kakodiya earned a Bachelor of Technology in Chemical Engineering from the Indian Institute of Technology, Bombay, completing his studies from 2016 to 2021. He possesses expertise in a variety of technologies, including Bert, Spacy, and Model-View-Controller (MVC). His educational background provides a strong foundation for his current work in machine learning.
Technical Skills and Proficiencies
Vaibhav Kakodiya is skilled in API design and has a solid foundation in SQL, Flask, and the Django Framework. He also has experience in Natural Language Processing and is proficient in Keras. His technical skills enable him to apply machine learning principles effectively to address complex business challenges.
Commitment to Continuous Learning
Vaibhav Kakodiya is committed to staying updated with the latest developments in the fields of artificial intelligence and machine learning. He has a strong background in data visualization, statistics, and probability, which supports his ongoing professional growth and ability to innovate in his work.