Jalaj Khandelwal
About Jalaj Khandelwal
Jalaj Khandelwal is a Machine Learning Operations Engineer at Uniphore, where he has worked since 2023. He has a background in data science and engineering, with experience in various roles at companies such as QpiAI and Tiger Analytics.
Work at Uniphore
Jalaj Khandelwal has been employed at Uniphore as a Machine Learning Operations Engineer since 2023. He works in a hybrid model from Bengaluru, Karnataka, India. In this role, he focuses on optimizing machine learning model performance for practical applications, contributing to the company's initiatives in enhancing AI-driven solutions.
Previous Experience in Data Science
Before joining Uniphore, Jalaj Khandelwal worked at Tiger Analytics as a Senior Analyst in Data Science from 2022 to 2023. He also served as a Data Scientist at QpiAI from 2021 to 2022, where he initially began his career as a Data Science Intern in 2020. His experience spans various roles that emphasize data analysis and machine learning.
Educational Background
Jalaj Khandelwal earned a Bachelor of Technology (BTech) degree in Electronics and Communications Engineering from the Indian Institute of Information Technology, Pune. His studies took place from 2016 to 2020, providing him with a solid foundation in engineering principles and technologies relevant to his career in data science and machine learning.
Internship Experience
Throughout his career, Jalaj Khandelwal has gained valuable experience through various internships. He worked as a Research Intern at the Indian Institute of Technology, Kanpur in 2019 and completed an internship at Doordarshan Kendra in 2018. Additionally, he was a Project Trainee at Bosch Engineering and Business Solutions in 2020 and served as a Data Analyst at Fitato in 2019.
Technical Expertise
Jalaj Khandelwal specializes in deploying machine learning solutions utilizing Docker and REST API technologies. He collaborates with cross-functional teams to drive innovation in machine learning projects, focusing on enhancing model performance for real-world applications.