Senior AI Engineer @ Impressit

7 days ago


Kraków, Czech Republic Impressit Full time

— 4+ years of commercial experience as a Machine Learning or AI Engineer— Strong proficiency in Python and experience with data handling libraries (NumPy, Pandas, SQL)— Proven experience in model deployment and serving using Flask, FastAPI, MLflow— Knowledge of LLM frameworks such as LangChain and LlamaIndex— Experience integrating with OpenAI, Anthropic, Cohere, or Mistral APIs— Familiarity with vector databases (FAISS, Pinecone, Weaviate, or Qdrant)— Understanding of Retrieval-Augmented Generation (RAG) systems— Good grasp of MLOps practices: model versioning, monitoring, and logging— Knowledge of LLM safety, including bias detection, moderation, hallucination mitigation, and prompt validation— Experience with CI/CD and deployment pipelines— Strong collaboration skills and ability to work in cross-functional teams— Upper-Intermediate or higher level of English Impressit is looking for an AI Engineer to join a cross-functional product team working on a digital transformation project that will revolutionize portfolio management and decision-making in the global trading domain. This is a great opportunity to contribute to a meaningful product with real-world impact, while working with modern AI technologies and international teams. As a plus: — Experience with Azure Cloud— Domain knowledge in Oil & Gas, Shipping & Trading, or ETRM systems— Familiarity with GenAI use cases: chatbots, copilots, document summarization, Q&A, and content generation— Strong understanding of model evaluation metrics (perplexity, relevance, user satisfaction)— Passion for responsible, explainable, and safe AI What about our benefits? — Generous vacation time: 24 days per year— Professional education and training budget— WOW team-building events— Paid sick leave We are waiting for you to join our WOW team ,[ Design, build, and deploy LLM-powered applications for trading and portfolio optimization use cases, Lead integration of GenAI and LLM technologies into existing systems, Implement retrieval-augmented generation (RAG) pipelines and vector database integrations, Develop and maintain model evaluation and monitoring pipelines (MLflow or custom dashboards), Work closely with data scientists, DevOps engineers, and product teams to deliver new AI-driven features, Contribute to rapid prototyping and MVP delivery for innovative GenAI solutions, Integrate solutions with Azure Cloud infrastructure and CI/CD environments, Ensure models meet performance, reliability, and responsible AI standards] Requirements: Python, LLM, RAG, Azure, GenAI Tools: Agile, Scrum.



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