THE ROLE & THE TEAM
We are looking for a Senior Machine Learning Engineer to enhance Zalando’s Machine Learning Ops Platform team, making them more scalable, efficient, and impactful. The primary focus of the work will involve contributing to the development, maintenance, and monitoring of MLOps Infrastructure, with key responsibilities including work on the Feature Store, Airflow pipelines, Databricks jobs, and associated observability systems. Additional tasks may be assigned as needed to support broader platform initiatives and evolving project requirements. Working closely with other Machine Learning Engineers, Data Scientists and Software Engineers, you will help shape the future of DARA ML & Data platform at Zalando.
WHAT WE'D LOVE YOU TO DO (AND LOVE DOING)Design and build foundational ML platform components, including systems for data access, feature management, model training, deployment, and inference at scale.
Develop infrastructure and tooling that enable ML practitioners to experiment, version, deploy, and monitor models in a reliable and automated way.
Architect scalable, modular, and reusable systems that serve as the backbone of ML development across multiple teams.
Implement core abstractions and APIs to standardize how ML workflows are executed - from feature creation to model rollout.
Build and maintain observability and reliability tooling for ML systems - including telemetry pipelines, model health checks, and automated retraining triggers.
Establish best practices, frameworks, and reference implementations that raise the bar for engineering rigor and speed in ML delivery.
Work closely with infrastructure, data, and security teams to ensure that ML systems are secure, compliant, and production-grade by default.
5+ years of experience in Spark, ML Ops, Data Engineering, AWS, Apache Airflow, Python.
Proven experience productionizing ML models and orchestrating ML workflows.
Experience with Databricks for scalable data processing and ML model training.
Strong collaboration and communication skills.
Bonus: Experience with feature stores and feature engineering pipelines.
At Zalando, our vision is to be inclusive by design. And this vision starts with our hiring - we do not discriminate on the basis of gender identity, sexual orientation, personal expression, ethnicity, religious belief, or disability status. You are welcome to leave out your picture, age, or marital status from your application. We only assess candidates on their qualifications and merit.
We want to provide you with a great candidate experience. Feel free to inform us of any accommodations you may need, so we can best support you throughout the hiring process.
do.BETTER - our diversity & inclusion strategy: https://corporate.zalando.com/en/our-impact/dobetter-our-diversity-and-inclusion-strategy
Our employee resource groups: https://corporate.zalando.com/en/our-impact/our-employee-resource-groups
Zalando provides a range of benefits, here’s an overview of what you can expect.
Employee shares program
40% off fashion and beauty products sold and shipped by Zalando, 30% off Zalando Lounge, discounts from external partners
2 paid volunteering days a year
Hybrid working model with 60% remote per week, actual practice is up to each team to best support their collaboration
Work from abroad for up to 30 working days a year
27 days of vacation a year (for Zalando SE)
Relocation assistance available (subject to prior agreement)
Family services, including counseling and support
Health and wellbeing options (including Gympass)
Mental health support and coaching available
Learn all about Zalando and our values here: https://jobs.zalando.com/en/?gh_src=22377bdd1us
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