Bachelorarbeit: DevOps/MLOps - Autolabeling Pipeline
Fill processes production data from many customer machines with cloud-based systems. Artificial intelligence methods are increasingly being used for this purpose. Since data situations and patterns to be recognized change again and again, a system must be created that extracts training and test data for AI models from the existing data catalog as needed in order to then train an improved model from it. The goal of this work is to create an automated system for data extraction from the data pool and importing the data into an existing data labeling system.
- Develop criteria to make the slow change in data distribution measurable.
- Creation of DevOps pipeline for data extraction based on these criteria.
- Eventual filtering of manually excluded data points.
- Incorporating already trained machine learning models to speed up labeling.
- Ongoing studies at a university of applied sciences/university
- Motivation & reliability
- Assumption of printing costs in case of very good or good results
- Support from a supervisor from the relevant specialist department
- Get to know Fill as a potential employer and contribute your own ideas and knowledge
- Great opportunity to supplement your theoretical knowledge with practical experience
- Very good working atmosphere in an award-winning family company
- Time frame: Start immediately
We look forward to receiving your application!