David Aponte sat down with Paperspace Senior ML Architect Misha Kutsovsky to talk about the future of MLOps and the architecture behind Gradient, Paperspace’s MLOps platform. Tune-in as David and Misha discuss the technical role of MLOps in the machine learning pipeline. They cover defining sensible primitives, abstracting away compute infrastructure, managing shared experiments from the CLI, collaborating via pull requests in shared repos -- and much more.
In this episode
Senior Machine Learning Architect, Paperspace
Misha Kutsovsky is a Senior Machine Learning Architect at Paperspace working on the Gradient team. He has expertise in machine learning, deep learning, distributed training, and MLOps. Previously he was on Microsoft's Windows Active Defense team building fileless malware detection software and tooling machine learning systems for Microsoft DevOps & Data Scientist teams. He holds B.S. and M.S. degrees in Electrical & Computer Engineering from Carnegie Mellon University.
David is one of the organizers of the MLOps Community. He is an engineer, teacher, and lifelong student. He loves to build solutions to tough problems and share his learnings with others. He works out of NYC and loves to hike and box for fun. He enjoys meeting new people so feel free to reach out to him!