AI Data Engineer - Warsaw - hybrid - B2B/UoP

EER Poland • Capon Bridge, WV

4h • Hybrid

About The Position

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.

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 Haves

• Experience in dynamic pricing or other high-frequency, data-intensive environments
• Contributions to open-source ML or data engineering projects

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level