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Rate 120 000 CZK - 160 000 CZK / month

Form of cooperation Full-time / 60% Remote

Sector Healthcare and Pharmacy

Location Praha

The reward is calculated upon delivery of 20 MD per month (1MD=8h)

Project duration 6 months with the possibility of extension

Period of cooperation 28.09.2026 - 27.03.2027

Start date 28.09.2026 or by agreement

Project duration 6 months with the possibility of extension

Period of cooperation 28.09.2026 - 27.03.2027

Start date 28.09.2026 or by agreement

Technology

Python
LLM Large Language Model
Prompt Engineering
RAG (Retrieval-Augmented Generation)
LLM Evaluation
Vector Databases
MLOps

Languages

Project description

design and development of robust and scalable internal AI systems
development of production generative AI and RAG solutions
leading significant AI development workstreams in the role of a senior technical specialist
selection and integration of suitable language models, vector databases, retrieval strategies and evaluation frameworks
optimization and fine-tuning of models in terms of performance, reliability, security and responsible AI
experimenting with RAG pipelines, prompt strategies and model-driven workflows
design and development of RESTful APIs for AI services
collaboration with tech leads, data scientists, platform teams, SMEs and business stakeholders
development of MLOps, CI/CD, observability, testing and lifecycle management of AI systems
collaboration in the ratio of 2 days onsite in Prague / 3 days remote

Project requirements

advanced experience with:
- development in Python
- designing, implementing and scaling production AI solutions
- RAG, LLM, vector databases, prompt engineering and generative AI applications
- building modern AI/ML pipelines
experience with:
- cloud services, data pipelines, databases and APIs
- CI/CD, MLOps, automated testing and model observability
- designing and developing RESTful APIs for AI services
- optimizing and fine-tuning models
advanced knowledge of:
- machine learning fundamentals including deep learning, optimization, evaluation and monitoring
- engineering best practices for developing maintainable production AI systems
knowledge of:
- responsible AI, security, reliability and lifecycle management of AI systems
- Agile working methods
advantageous:
- Bachelor's or Master's degree in Artificial Intelligence, Machine Learning, Computer Science or a quantitative field

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