Senior Machine Learning Engineer – Demand Forecasting (all genders)

THE ROLE & THE TEAM

Zalando fulfills more than a hundred million customer orders every year and volumes are increasing. Fulfillment Core within Zalando builds and operates systems that are at the core of Zalando’s platform strategy and ensure timely, efficient, and correct delivery of every one of our customers’ 185+ million orders every year.

Enabling the fulfillment of orders is a complex process, involving the choice of physical locations of our warehouses and the placement of stock, the planning of inner warehouse processes and capacity management, the management of a diverse range of fulfillment and delivery configurations, all while optimizing towards various competing targets.

Demand forecast is at the heart of these processes, where the forecasted demand of a given article would play an essential role to determine, for example, in which warehouse and where inside that warehouse the article should stay.

As a Senior Machine Learning Engineer, you will play an essential role in defining and managing the next generation of our engineering infrastructure (e.g. data ETL pipelines, train/inference deep learning model pipelines, and many more). You will be part of a skilled team of ML engineers and applied scientists to address complex forecasting challenges, improve the precision of demand predictions, and support many highly-important strategic and data-driven use-cases, such as inventory optimization inside warehouses and across a network of warehouses. This role offers a unique chance to be at the forefront of Zalando\’s technological advancement, enhancing your engineering expertise in a high-impact and dynamic environment.

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)

1. Work closely with applied scientists to deploy ML models to a production environment.
2. Design, build, and maintain ML models and its data pipelines.
3. Utilize a cloud-based tech stack including SageMaker, Databricks, and AirFlow.
4. Implement best practices in software engineering, including code quality and testing for the Python codebases.
5. Ensure system stability and improve monitoring and resilience.
6. Mentor others, drive innovation, and foster a positive and inclusive work environment.
7. Be part of Zalando’s engineering community and advocate team’s processes.

YOU HAVE

1. Extensive industry experience in designing, developing and operating data-intensive ML systems.
2. Experience working together with applied scientists, and familiar with traditional applied science processes from ideation to productionisation. Basic knowledge of ML concepts such as training vs inference, backtesting, model monitoring, etc.
3. Proficiency in Python and with data processing and analysis tools like PySpark, Pandas and Numpy and experience using deep learning frameworks such as PyTorch.
4. Familiarity with CI/CD tools, container/orchestration tools such as AWS (EKS, ECS), Kubernetes, Docker and other data processing and analysis tools like SageMaker, Databricks and Airflow.
5. Eagerness to collaborate with applied scientists to test and productionize new ML approaches.
6. Team player and highly self-motivated, with a strong sense of ownership and accountability.
7. Fluency in English and excellent technical communication skills to present complex technical information in a clear and concise manner.

OUR OFFER

Zalando provides a range of benefits, here’s an overview of what you can expect. Ask your Talent Acquisition Partner to learn more about what we offer.

1. Employee shares program.
2. 40% off fashion and beauty products sold and shipped by Zalando, 30% off Zalando Lounge, discounts from external partners.
3. 2 paid volunteering days a year.
4. Hybrid working model with up to 60% remote per week, actual practice is up to each team to best support their collaboration.
5. Work from abroad for up to 30 working days a year.
6. 27 days of vacation a year to start.
7. Relocation assistance available (subject to prior agreement).
8. Family services, including counseling and support.
9. Health and wellbeing options (including Gympass).
10. Mental health support and coaching available.
11. Drive your development through our training platform and biannual peer-to-peer review.

Please note that all applications must be completed using the online form – we do not accept applications via e-mail.

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