Junior / Middle NLP Engineer

Location: • Europe, Remote
• Zagreb, Croatia

Category: • NLP
• ML
• RAG

What's the Project?

NLP Engineer
Take the opportunity to work with high-professional people with remarkable ideas on their minds!
Our Client is one of the innovative healthcare software providers founded by a physician-led team passionate about solving the burden of prior authorizations. Imagine the frustration of prior authorizations: as patients, as physicians, and as healthcare executives. We facilitate extracting patient`s data from medical documents. The idea is to decrease the time to fill medical insurance forms after the clinic visit and make the treatment process fast and comfortable. At its core, Natural Language Processing service drives the recognition of medical documents. You will be part of the team of professionals who develop the technology to simplify day-to-day operations.

You Perfectly Match If you have:

Theoretical understanding and practical experience of classical NLP, Neural Network driven NLP and LLM’s / RAGs
Theoretical knowledge and practical experience with basic NLP text processing
Strong understanding of Deep learning and model architectures.
Bachelor’s degree or higher in a technical field of study
Intermediate + English level
Python NLP libraries (Spacy, Flair, etc)
The theoretical foundation of algorithms
Experience with Git
Understanding of security/access control, scalability, high availability, and concurrency patterns.
Ability to clearly explain and justify ideas when faced with competing alternatives
Ability to write consistent and easily maintainable Python code.
Understanding of object-oriented programming
Ability to study new technology

Your day-to-day activities:

Work with the NLP team to design, build, and maintain efficient, reusable, and reliable code.
Identify and resolve bottlenecks and bugs in the NLP part of the project
Work with classical NLP algorithms, analyze text data, train new and tune existing models
Develop and deploy cutting-edge language models (LLMs) to solve real-world problems.
Fine-tune, optimize and evaluate LLMs for various applications.
Help maintain code quality, organization, and automatization
Follow and help refine the development of best practices and standards

Junior: Assist in the development and deployment of language models (LLMs). Learn to fine-tune, optimize, and evaluate LLMs for different tasks. Gain practical experience in NLP, deep learning, and LLM architectures.