AI Data Engineer - Warsaw - hybrid - B2B/UoP

We are looking for a hands-on, ownership-driven AI Data Engineer to play a key role in building and scaling the data infrastructure behind an advanced AI engine (Large Market Model – LMM). This position sits at the intersection of Data Engineering, Machine Learning, and MLOps. You will design and operate production-grade data and modeling pipelines that transform large-scale, complex datasets into predictive intelligence. Responsibilities Design and build scalable, AI-ready data pipelines ingesting diverse structured and unstructured datasets Develop advanced feature engineering pipelines in collaboration with domain experts Implement and maintain distributed data processing systems (e.g., Spark, Dask) Build robust data validation and model evaluation frameworks Monitor production systems for model performance, reliability, and data drift Own CI/CD processes for ML pipelines and deployments Optimize end-to-end ML workflows from ingestion to serving Continuously research and experiment with improvements in feature engineering, MLOps, and model optimization Requirements 2+ years of commercial experience building production-level AI/ML data systems Strong proficiency in Python and the ML/data ecosystem (Pandas, Scikit-learn) Experience with distributed computing frameworks (Spark, Dask, etc.) Hands-on experience designing and maintaining SQL-based ETL pipelines Practical experience with MLOps principles and orchestration tools (e.g., Airflow, Dagster) Solid software engineering fundamentals Experience with containerization (Docker) Experience working with cloud platforms (AWS, GCP, or Azure) Strong problem-solving and communication skills B.Sc . or M.Sc . in Computer Science, Engineering, Mathematics, or a related quantitative field Nice to Have Experience in dynamic pricing or other high-frequency, data-intensive environments Contributions to open-source ML or data engineering projects