Machine Learning Engineer, Team Leader

Xebia is a global tech company in the CEE region, originating from two Polish companies, PGS Software and GetInData, with over 1,000 experts specializing in cloud, data, and software projects. They deliver scalable platforms, data and AI solutions, and applications across industries including fintech, e-commerce, aviation, logistics, media, and fashion. Their clients include McLaren, Aviva, Deloitte, Spotify, Disney, and others. Xebia is a trusted partner of Databricks, dbt, Snowflake, Azure, GCP, and AWS, recognized as the first AWS Premier Partner in Poland.

• 8+ years of experience in Machine Learning or Data Science roles in production environments
• 2+ years of direct people management experience
• Proven track record in leading end-to-end model training initiatives for business use cases
• Strong expertise in the full model lifecycle: data preparation, feature engineering, training, evaluation, calibration, and controlled rollout
• Hands-on proficiency in Python and SQL
• Strong understanding of ML/deep learning frameworks such as PyTorch or TensorFlow
• Experience with scalable data processing workflows
• Experience operating ML workloads in cloud environments, preferably GCP (Vertex AI, BigQuery, Cloud Storage)
• Ability to drive cross-functional execution across ML, serving, and product domains
• Strong decision-making based on business metrics (revenue, GMV, conversion) and experimentation results
• Very good command of English, both written and spoken
• Openness to on-site workshops up to 1-3 per quarter in Warsaw

Nice to have:

• Experience in AdTech, marketplace ranking, or recommendation systems at scale
• Familiarity with model artifact repositories, CI/CD for ML, experiment tracking frameworks, and feature store integrations
• Exposure to online inference environments and cooperation with platform teams maintaining such services
• Experience with developing pCTR/pCVR-like models

• Ensuring the team delivers high-quality ML scoring solutions (e.g., click and conversion predictions) on schedule
• Maintaining responsibility for the team's technical output and project milestones
• Managing the training scope for deep learning models, including feature space definition and model lifecycle standards
• Orchestrating the transition of scoring responsibilities from existing teams in cooperation with backend and product stakeholders
• Providing expert insight to future roadmaps for the ML scope

Work from the European Union region and a work permit are required.