Maciej Mazur
About Maciej Mazur
Maciej Mazur is a Principal Machine Learning Engineer at Canonical, specializing in deploying Kubernetes for AI and high-performance computing. He has extensive experience in various roles within the tech industry, including positions at Nokia Networks, Hewlett Packard Enterprise, and ETSI.
Current Role at Canonical
Maciej Mazur serves as a Principal Machine Learning Engineer at Canonical, a position he has held since 2022. In this role, he focuses on deploying Kubernetes at scale for artificial intelligence and high-performance computing. He also manages distributed compute pools utilizing bare metal Kubernetes on edge, ensuring efficient resource allocation and performance optimization.
Previous Experience at Nokia Networks
Maciej Mazur has extensive experience at Nokia Networks, where he held multiple roles. He worked as a Technical Product Manager from 2015 to 2017, and prior to that, he was a System Architect for nine months in 2014. Additionally, he served as a Software Engineer from 2013 to 2014 and as a Senior Integration & Verification Engineer from 2011 to 2013. His tenure at Nokia Networks provided him with a solid foundation in telecommunications and systems architecture.
Experience at Hewlett Packard Enterprise
From 2017 to 2019, Maciej Mazur worked at Hewlett Packard Enterprise as a Lead Solutions Architect. In this role, he was responsible for designing and implementing solutions that met customer needs, leveraging his technical expertise to drive project success in a remote work environment.
Education and Expertise
Maciej Mazur studied at Wroclaw University of Science and Technology, where he earned a Master of Science in Electronics from 2005 to 2010. His educational background supports his specialization in deploying Kubernetes for AI and high-performance computing, as well as his expertise in low-level NVidia GPU coding and tuning for machine learning projects.
Involvement with ETSI and Canonical
Maciej Mazur served as the VNF On-Boarding TF Chair for ETSI OSM from 2021 to 2022, contributing to the development of standards in network functions virtualization. Additionally, during his time at Canonical, he represented the company in AI and machine learning discussions with partners, customers, and communities, further establishing his role in the tech industry.