Junior / Middle NLP Engineer

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.

• 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

• 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.