Ken Lorbetskie

Ken Lorbetskie

Machine Learning Operations (Ml Ops) Specialist Co Op @ Kelvin Zero

About Ken Lorbetskie

Ken Lorbetskie is a Machine Learning Operations (MLOps) Specialist Co-Op currently working at Kelvin Zéro in Ottawa, Ontario. He has a background in Electrical Engineering and Computing Technology from the University of Ottawa and has held various roles in data analytics and machine learning development.

Work at Kelvin Zero

Ken Lorbetskie currently holds the position of Machine Learning Operations (MLOps) Specialist Co-Op at Kelvin Zéro. He has been with the company since 2021, contributing to projects that focus on the integration and deployment of machine learning models. His role involves optimizing machine learning workflows and ensuring efficient operational processes within the organization.

Previous Experience in Data Analytics

Prior to his current role, Ken worked as a Data Analytics Intern at the National Research Council Canada in 2019. During this three-month internship in Ottawa, Ontario, he gained experience in data analysis techniques and contributed to various research projects, enhancing his skills in data-driven decision-making.

Experience as Machine Learning Platform Developer

Ken served as a Machine Learning Platform Developer Co-Op at Kinaxis in 2020. He completed two separate three-month terms in the Ottawa, Canada area, where he focused on developing and implementing machine learning solutions. His work involved collaborating with teams to improve platform capabilities and support data analysis initiatives.

Role in University of Ottawa Rover Team

From 2019 to 2021, Ken was the Software Technical Lead for the University of Ottawa Rover Team. In this capacity, he led software development efforts for the team's projects, overseeing the technical aspects and ensuring the successful implementation of software solutions for rover operations.

Education and Expertise

Ken Lorbetskie studied at the University of Ottawa, where he earned a Bachelor of Applied Science (BASc) in Electrical Engineering and Computing Technology. His academic journey spanned from 2017 to 2022, providing him with a solid foundation in engineering principles and computing technologies relevant to his career in machine learning and data analytics.

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