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, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.
In the CEE region, we’re 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, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing.
You will be:
- driving the design, refinement, and evaluation of ML scoring models (e.g., CTR, CVR, and RoAS), integral to core bidding logic,
- design architecture of model strategies for complex solutions integrating user, product, and placement signals, ensuring readiness for high-throughput and low-latency environments,
- collaborating with engineering and business stakeholders to translate strategic goals into measurable modeling outcomes and technical roadmaps,
- providing technical leadership and quality assurance for Data Science workstreams within the project scope to ensure alignment with production standards.
Your profile:
- extensive hands-on experience in designing, training, and improving Deep Learning models for business-critical production use cases,
- proven expertise in deep learning frameworks such as PyTorch or TensorFlow, as well as strong practical knowledge of Pandas and NumPy,
- advanced SQL skills, preferably including analytical SQL used in large-scale data environments,
- strong experience with public cloud infrastructure, preferably Google Cloud Platform, including ML oriented services such as Vertex AI and Vertex Pipelines,
- proven ability to lead end-to-end model development, from problem framing and feature design to evaluation and production handoff,
- strong engineering foundations, including writing production-level, testable, and documented Python code, with familiarity with CI/CD practices,
- ability to mentor other Data Scientists and raise modeling standards across the team,
- relevant academic degree or extensive professional experience in a STEM field (e.g. Computer Science, Mathematics, Mathematical Statistics, Quantitative Methods, or Physics),
- openness to on-site workshops max 1-3 per quarter in Warsaw.
Work from the European Union region and a work permit are required.
Nice to have:
- experience in developing ML models for low-latency online applications,
- experience within the advertising or marketing domains,
- demonstrated experience in developing ML models for predicting business events like clicks or conversions (i.e., Click-Through Rate (CTR) and Conversion Rate (CVR) modelling),
- proficiency in traditional machine learning techniques, such as Gradient Boosted Trees,
- experience in mentoring, technical leadership, or coordinating model development across a broader team,
- practical use of AI-assisted coding tools to improve engineering productivity and quality.
Recruitment Process:
CV review – HR call – Interview – Client Interview – Decision
