Must have

• Use cases

• NLP

• Python

• MLOps

• Cloud

• AWS

• GCP

• Azure

• AI

• Machine learning

• Polish

• English

Requirements description

• Minimum 3 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 - MUST HAVE

• 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

Offer description

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
• A long-term collaboration with opportunities for growth and development

Your responsibilities

1. Model Development & Fine-Tuning: Design, train, fine-tune, and evaluate large language models (LLMs) using domain-specific or proprietary data to meet business needs.
2. Prompt Engineering: Craft, test, and optimize prompts to improve model outputs
3. LLM Integration: Deploy and integrate LLMs into production applications, including agentic solutions, RAG, chatbots, designing APIs, latency/throughput optimization, and monitoring.
4. Research & Experimentation: Stay current with state-of-the-art LLM architectures and techniques, and evaluate their application for internal use cases.
5. 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.