Position: Machine Learning Engineer
Company: COMPARUS
Category: Python
Experience required: 1y
English level: intermediate

Project:

Artificial intelligence: text document recognition and document classification based on machine learning and CFS platform

Customer: representatives of German financial branch

Job Overview: Developing and testing complex machine learning pipelines

We offer:

- enough work for all team players
- the possibility of business trips to Germany
- you can make your work interesting, we promote that
- cutting-edge technologies are welcome in our team
- we will try to motivate you as much as we can if you need that
- we know, that developers love hardware, we will try to make you happy with your working place
- friendly-professional atmosphere in a team, we like to work together :)
- there is no 9−18 schedule, unless it is adequate
- you can enjoy your vacation in the same way and amount as most of your friends
- when you are sick, we are sad with that and of course compensate it as working time

Our requirements:

- Machine learning (PyTorch, TF, OpenCV, PIL, Flair)
- Data Processing (Converting training data between different formats, complex pipelines)
- Software development (Python3, basic design patterns, HTTP, REST API).
- Solid experience in software engineering: modern software development practices and tools, concurrent and distributed programming, operating systems, computer networks, database systems
- Docker (Optimized images, docker-compose)
- Git workflow (branching, merging)
- English language (B1-B2)
- Ability to work independently and high attention to detail

Will be a plus:

- PDF processing experience
- Bachelor’s degree in Computer Science/Computer Engineering
- Strong communication skills and experience being a flexible team player

Responsibilities:

- Working with NLP, CV especially NER, Instance Segmentation, Classification tasks.
- Develop and test ML models and CLI for training pipelines.
- Working with WebServices (Flask)
- Creating Docker containers
- Data Visualization and Presentations