LLM Avalanche: Maria Vechtomova · Why is MLOps (and LLMOps) booming and how you can catch up?

ai.bythebay.io Nov 2025, Oakland, full-stack AI conference 10 years ago, most corporate companies started investing in data science, they created their first data science teams and were waiting for the investment to pay off. Unfortunately, many data science projects ended up failing because data scientists did not have knowledge to bring their models in production, and teams that could (for example, DevOps/ software engineers) were very far from the data science teams within the organization and lacked machine learning knowledge. Things changed after Machine Learning Engineer role emerged and MLOps came in place. Following MLOps standards significantly reduce time to production. In large organizations, it quickly pays off. In this talk I will talk about pragmatical approach to MLOps and how to get started with it. I will touch on specific case of deploying LLMs in a corporate setting.