🚀 Senior ML Software Engineer - Growth & Lifecycle (all genders) at Zalando in Berlin - Scaling Machine Learning Growth

Stichworte

• MachineLearning
• Python
• Spark
• Databricks
• AWS
• Berlin
• Personalization
• MLOps
• BigData
• Full-time

Zusammenfassung

Zalando sucht für sein Lounge-Team in Berlin einen erfahrenen Senior ML Software Engineer zur Verstärkung des Growth & Lifecycle Bereichs. In dieser Schlüsselposition entwickeln und skalieren Sie Personalisierungssysteme, die Millionen von Mitgliedern über verschiedene Kanäle hinweg erreichen. Ihr Fokus liegt auf dem Aufbau robuster Feature-Pipelines und der Implementierung von Machine-Learning-Modellen in einer produktiven Big-Data-Umgebung. Durch den Einsatz moderner Tools wie Spark, Databricks und KI-gestützter Workflows treiben Sie die Automatisierung des Marketings maßgeblich voran. Werden Sie Teil eines innovativen Teams, das echten Impact durch datengesteuerte Entscheidungen und technologische Exzellenz schafft.

Benefits und Qualifikationen

• 40% Mitarbeiter-Rabatt
• 30% Lounge-Rabatt
• Aktienprogramm
• Umzugshilfe
• 27 Tage Urlaub
• Spark und Databricks Kenntnisse
• AWS SageMaker Erfahrung
• Python Expertise

Stellenausschreibung

The Role & The Team

Lounge by Zalando is a leading online shopping club for fashion and lifestyle, providing millions of members across Europe with exclusive daily sales. The Growth & Lifecycle team serves as the company's growth engine, converting traffic into loyal, high-lifetime-value customers. At the core of this mission is advanced personalization, determining the optimal campaign sequence for every member across push, email, and on-site touchpoints.

We are looking for a Senior ML Software Engineer to spearhead our machine-learning infrastructure. You will expand our personalization capabilities from single-channel to multi-channel systems, starting with email integration via Braze. Your work will involve building sophisticated feature pipelines, training workflows, and scalable batch inference systems, all while utilizing AI-native coding tools to accelerate development and ensure high quality.

What You Will Do

• Lead end-to-end personalization by taking ownership of production models and evolving them for multi-channel reach.
• Architect and implement large-scale feature engineering pipelines using Spark and Databricks.
• Operate scalable inference services handling millions of requests, focusing on high throughput and cost optimization.
• Measure and prove business impact through rigorous A/B testing and incrementality analysis.
• Integrate data-science models like churn and propensity into real-time customer touchpoints to drive autonomous marketing.
• Mentor junior and mid-level engineers while establishing high technical standards for the entire team.

Your Profile

• Proven track record in productionizing machine learning systems, including feature pipelines and model serving.
• Expertise in big-data processing with Spark and Databricks, specifically for recommendation or ranking systems.
• Deep professional proficiency in Python; experience with JVM languages like Kotlin is a benefit.
• Experience with cloud-native ML Ops on AWS, including SageMaker, Kubernetes, and CI/CD.
• Strong focus on experimentation rigor and the ability to defend evaluation metrics.
• Efficiency in using AI-assisted engineering workflows to speed up validation and development.
• Excellent communication skills to resolve ambiguity and lead cross-functional projects.

Our Offer

• Participation in the employee shares program.
• Substantial discounts of up to 40% on Zalando and 30% on Lounge products.
• 27 days of annual vacation for a balanced work-life ratio.
• Relocation support and comprehensive family services.
• Access to health and wellbeing platforms, including mental health coaching.
• Continuous growth opportunities through dedicated training and peer reviews.