Responsibilites
- Model Development & Fine-Tuning: Design, train, fine-tune, and evaluate large language models (LLMs) using domain-specific or proprietary data to meet business needs.
- Prompt Engineering: Craft, test, and optimize prompts to improve model outputs
- LLM Integration: Deploy and integrate LLMs into production applications, including agentic solutions, RAG, chatbots, designing APIs, latency/throughput optimization, and monitoring.
- Research & Experimentation: Stay current with state-of-the-art LLM architectures and techniques, and evaluate their application for internal use cases.
- Stakeholder Collaboration: Collaborate with product, data, and engineering teams to translate business problems into LLM-powered solutions and communicate model limitations or trade-offs effectively.
Requirements
- Minimum 2 years of hands-on experience with LLMs, NLP, or foundation model development in an industry setting.
- Deep understanding of transformer-based models and modern NLP techniques.
- Proficiency in Python and experience with common LLM/NLP libraries and frameworks
- Experience with fine-tuning and serving LLMs
- Familiarity with vector databases and retrieval-augmented generation (RAG) pipelines
- Experience with MLOps, cloud infrastructure (AWS/GCP/Azure), and model deployment tools for LLM-based systems.
What We Offer
- Deep understanding of the domain knowledge in the field of molecular biology and biotechnology
- Exposure and hands on experience in the development of modern cloud data solutions
- Ability to deliver AI and ML solutions at scale
- Opportunity to work in an experienced and engaged team consisting of Data Engineers, Data Scientists, Machine Learning Engineers and stakeholders from different business domains
location: Wroclaw (hybrid)
start: August-October
seniority: 2+ years experience