Principal Applied Scientist / Lounge by Zalando (all genders)

Role: The Principal Applied Scientist will work across the team that builds the customer‑facing fashion assistant and personalized landing page, focusing on recommendation systems and agentic development. This individual will define evaluation metrics, develop custom ML models and LLM‑based solutions, and contribute to production‑grade software. Responsibilities: - Use LLM APIs to create the ideal fashion assistant for customers. - Develop and improve machine‑learning applications such as personalized recommendation systems. - Translate ambiguous business challenges into research questions, define solutions, and lead end‑to‑end applied‑science strategy, including model selection, problem formulation, training and inference. - Develop and implement evaluation frameworks to assess impact, analyze customer behavior and business performance. - Leverage AI coding tools to deliver software at a fast pace. Qualifications: - Strong expertise in production ML applications with at least 3 years of hands‑on experience building and deploying scalable, high‑performance recommendation or search solutions. - Minimum 5 years of software‑engineering experience using Python. - Experience with LLM application development and evaluation (highly desired). - Excellent knowledge of machine learning, statistics and online A/B testing. - Hands‑on experience with deep learning, gradient‑boosting trees, vector search (e.g., PyTorch, TensorFlow, CatBoost, FAISS). - Practical experience with large‑scale data processing and deploying ML models to production, especially real‑time APIs (Databricks, Spark, Flink, Beam, SageMaker, Kubernetes, REST APIs). What We Offer: - 27 days of holiday (up to 30 days with seniority) and 2 paid volunteering days. - Hybrid working model with up to 60 % remote and the possibility to work from abroad up to 30 days per year. - Employee share program, 40 % discount on fashion and beauty products, 30 % discount on Lounge by Zalando and external partner offers. - Relocation assistance, family services, health and wellbeing options, mental‑health support and coaching. - Development opportunities through a training platform and bi‑annual peer‑to‑peer reviews.