Machine learning algorithms and software have become more accessible to more organizations in the past decade.
Better tooling enables easier experimentation, and many engineering teams are now moving their models from ML notebooks to production ML systems. However, there are many challenges in production machine learning, and “only 22% of companies using machine learning have successfully deployed a model” (The Batch).
To help more teams successfully deploy models, we’re starting a new MLOps engineering blog (https://blog.citadel.co.jp) to discuss the challenges and best practices of production machine learning. We hope you’ll find it useful when developing, testing, and deploying your ML systems.
(Note: The engineering blog is currently only available in Japanese.)
【About Citadel AI Inc.】
Citadel AI is a startup in Tokyo, and raised a seed round in 2021 from The University of Tokyo’s Innovation Platform (UTokyo IPC) and ANRI. Our engineering team is led by the former head of AI infrastructure development at Google Brain.
We’re actively recruiting talented software engineers to build the future of reliable AI systems – apply here!