Machine Learning Engineer (personalization) m/f/d

Description

As a Senior Machine Learning Engineer in the Machine Learning Shop team, you will own the business-critical logic behind a campaign-based flash-sale model. Your work will directly impact campaign ranking based on customer interests and category affinities, product recommender systems, and churn prevention through communication models.

You will work in a modern tech-stack environment and agile setup alongside Product Owners, Data Engineers, and Web Developers.

Main Tasks

• Build and deploy data-driven and machine-learning solutions for portal personalization and campaign ranking.
• Manage the full machine-learning process: verify data quality, select algorithms, engineer features, validate models with appropriate metrics, and ensure interpretability.
• Monitor, maintain, scale, and update existing data and ML pipelines.
• Build solutions using software best practices, including clean code, testing, and automated deployments.
• Collaborate with data engineers, data scientists, and development teams to build reliable data pipelines and shared, clean data sources.
• Explain and recommend data-driven and ML solutions to business stakeholders and developer teams.
• Share and improve ML and MLOps knowledge across the organization.

Requirements

• 3–5+ years of professional experience building, training, validating, and deploying ML solutions in production environments.
• Very good knowledge of Python, SQL, and Git.
• Experience training and validating ML solutions, including decision trees, neural networks, and regression models.
• Ability to scale solutions according to infrastructure and business requirements.
• Good understanding of data lake/lakehouse architecture.
• Good English skills at C1 level for an international work environment.

Nice to Have

• Experience with recommender systems and NLP.
• Experience with e-commerce data ecosystems.
• Experience with PySpark and the Databricks Lakehouse platform ecosystem.
• Experience with structured streaming and Scala.
• Familiarity with MLOps environments such as MLflow.

Benefits

• Hybrid or remote work model: work two days per week from the Wrocław office if based locally, choosing the days, or work fully remotely from anywhere in Poland.
• Flexible start times.
• Product benefits, a wellbeing platform with health programs, webinars and challenges, private medical care (Lux Med) for you and your family, and a Multisport card.
• Office amenities including a desk treadmill, ping-pong table, popcorn machine, Xbox console, and massage mat. Children and pets are welcome in the office.
• Access to language learning in English, German, and Polish, plus courses, podcasts, learning tools, international projects, collaboration, and occasional business trips.
• Eco-friendly office practices.
• Sports events, team gatherings, company-wide events, and casual afterwork events.