Tajinder Tajinder
About Tajinder Tajinder
Tajinder is a Principal Machine Learning Ops Engineer currently working at OneTrust in Bengaluru, India. He has a background in software engineering and machine learning, with previous roles at Dataguise and Spice Money, and holds degrees in Computer Science and Machine Learning.
Current Role at OneTrust
Tajinder currently serves as a Principal Machine Learning Ops Engineer at OneTrust, a position he has held since 2023. He operates remotely from Bengaluru, Karnataka, India. In this role, he focuses on leveraging machine learning operations to enhance data management and compliance solutions.
Previous Experience at Dataguise
Before joining OneTrust, Tajinder worked at Dataguise, which is now part of PKWARE, as a Senior Software Engineer from 2019 to 2021. His tenure at Dataguise was based in Mohali, where he contributed to the development of data security solutions.
Professional Background at Spice Money
Tajinder's career includes significant experience at Spice Money, where he held multiple roles over six years. He started as a Software Engineer Trainee in 2013 and progressed to Database Developer. From 2021 to 2023, he served as Data Science Manager, overseeing data science initiatives and team management.
Education and Expertise
Tajinder holds a Bachelor's degree in Computer Science from Maharishi Markandeshwar (Deemed to be University), completed between 2008 and 2012. He furthered his education with a Master of Science in Machine Learning and Artificial Intelligence from Liverpool John Moores University, graduating in 2023. Additionally, he earned a PG Diploma in Machine Learning and Artificial Intelligence from the International Institute of Information Technology Bangalore in 2022.
Technical Skills and Contributions
Tajinder has developed encryption and masking solutions for various data platforms, utilizing programming languages such as Java, Python, and DotNet. He has contributed to the research and implementation of machine learning algorithms and tools, employing MLOps tools like MLFlow and Azure Machine Learning to streamline model deployment and monitoring.