Remove Data Integration Remove DevOps Remove ML Engineer Remove Software Engineer
article thumbnail

MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Data storage and versioning You need data storage and versioning tools to maintain data integrity, enable collaboration, facilitate the reproducibility of experiments and analyses, and ensure accurate ML model development and deployment. Easy collaboration, annotator management, and QA workflows.

Metadata 134
article thumbnail

Learnings From Building the ML Platform at Mailchimp

The MLOps Blog

I started from tech, my first job was an internship at Google as a software engineer. I’m from Poland, and I remember when I got an offer from Google to join as a regular software engineer. I switched from analytics to data science, then to machine learning, then to data engineering, then to MLOps.

ML 52