ml engineer in fintech

XTB is a global financial company focused on online trading of financial instruments. It operates across several countries, including markets in Asia and South America, and is a leading FinTech in Poland and Central and Eastern Europe.

• Implement and maintain end-to-end AI solutions focused on robust and scalable LLM pipelines and agentic workflows;
• Develop and optimize RAG systems and AI agents using modern frameworks;
• Build and integrate production-grade APIs, including gRPC and MCP, for the global trading platform and internal business units;
• Measure agent performance using LLMOps tracing, MLOps evaluations, latency, and error-rate metrics;
• Apply evaluation-driven development with RAG-eval, LLM-as-a-judge techniques, and model benchmarking;
• Collaborate with Product and Data teams to build and maintain MCP servers and data-serving layers with real-time enterprise data;
• Maintain code quality through unit tests, linters, type-checkers, documentation, and code reviews;
• Leverage Claude Code and Codex in daily development and share learnings with the team.

• 2–5 Years of commercial experience in AI/ML or Software Engineering with systems deployed to production;
• Modern Python skills and understanding of AI Agent architectures, including context engineering, tool calling, skills, and agent loops;
• Hands-on experience developing MCP servers or custom tool-calling interfaces;
• Practical experience with LLM orchestration and data frameworks such as LangGraph or LangChain;
• Experience building and maintaining production-grade REST, gRPC, and MCP APIs;
• Understanding of PostgreSQL, pgvector, and semantic, hybrid, and BM25 search strategies;
• Familiarity with MLOps and LLMOps, including MLflow or Langfuse, automatic evaluations, and prompt optimization;
• Strong communication and collaboration skills in an Agile, cross-functional environment;
• English for professional collaboration;
• Experience monitoring application health and performance with Prometheus and Grafana;
• Nice to have: AI Agent evaluation, dataset curation, statistical metrics with confidence intervals, LLM-as-a-judge calibration, financial systems or trading, regulated fintech, LLM red teaming, adversarial testing, anti-jailbreak policies, context compression, prompt caching.

• Real influence on company and product development;
• Experienced team with knowledge sharing;
• Regular feedback and clear career paths;
• Regular team-building meetings;
• Training budget for courses and conferences;
• Extra day off on your birthday;
• Extra day off for parents;
• Equipment tailored to your needs;
• Private medical care and group insurance;
• Access to an English e-learning platform and benefits platform;
• Access to a wellbeing platform, workshops, and private therapy sessions;
• Remote work from the office in Warsaw or from a coworking space in your city.