Machine Learning Engineer, Team Leader

Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products. In the CEE region, we are a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake.

• 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 practical expertise in the full model lifecycle: data preparation, feature engineering, training, evaluation, calibration, and controlled rollout
• Hands-on proficiency in Python and SQL, with strong understanding of ML/deep learning frameworks (e.g., pytorch or tensorflow) and scalable data processing workflows
• Experience operating ML workloads in cloud environments, preferably GCP (Vertex AI, BigQuery, Cloud Storage)
• Proven ability to drive cross-functional execution across ML, serving, and product domains, ensuring strategic alignment and performance visibility for stakeholders
• Strong decision-making based on business impact metrics (revenue, GMV, conversion) and experimentation results
• Very good command of English, both written and spoken
• Openness to on-site workshops max 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

Team leadership and delivery:

• Ensure that the team delivers high-quality ML Scoring solutions (e.g., click and conversion predictions) on schedule
• Maintain responsibility for the team's technical output and project milestones

Model training and lifecycle:

• Manage the training scope for deep learning models, including feature space definition and model lifecycle standards

Collaboration and roadmap:

• Orchestrate the transition of scoring responsibilities from existing teams in cooperation with backend and product stakeholders
• Provide expert insight to future roadmaps for the ML scope

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