Senior ML Software Engineer

Zalando

Shop the latest fashion & shoes online | Free delivery* & returns on most of the orders | Over 1,900 Brands – new products every day!

At Zalando, our vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce – one that is inclusive by design. We only assess candidates based on qualifications, merit, and business needs. We welcome applications from people of all gender identities, sexual orientations, personal expressions, racial identities, ethnicities, religious beliefs, and disability statuses.

As a senior engineer in data and machine learning in our Transaction Risk Management team, you will have the opportunity to join a dynamic and diverse group of product managers, engineers, and applied scientists. As part of our team, you will have the chance to work on cutting edge projects and innovative technologies, raise the technical bar, improve our operational excellence, and shape our ways of working.

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

1. Participate in the full development life cycle, end-to-end, from design, implementation and testing, to documentation, delivery, support, and maintenance.
2. Implement, operate, and continuously improve large-scale data pipelines for batch and real-time processing to enable risk inference and risk assessment.
3. Increase the operational excellence of our data pipelines by using best practices for data quality assurance, testing, monitoring, alerting, and cost efficiency.
4. Support the development of a feature store, consisting of features for risk inference and risk assessment.
5. Own the design, development, and maintenance of ongoing metrics, reports, analyses, and dashboards to drive key business decisions.
6. Deploy, operate, and continuously improve our large-scale machine learning services for detecting transactional risks, including batch and real-time inference, on cloud-based infrastructure.
7. Responsible for team’s end-to-end MLOps, productionizing machine learning services, including workflow automation and orchestration.
8. Tackle challenges for developing algorithms and running them efficiently on cloud-based infrastructure.
9. Increase operational excellence of our machine learning services by introducing best practices for model testing, experimentation, versioning, serving, retraining, monitoring and alerting.

Minimum Requirements:

1. 5+ years of hands-on experience as a software engineer, data engineer, or machine learning engineer that productionized and operated data pipelines, machine learning models for large-scale services in cloud environments (preferably AWS).
2. Proficiency in Python, SQL (expertise in Java and Scala is preferred).
3. Experience in designing, developing, and operating highly-scalable microservices (API design) on a distributed system.
4. Knowledge in automated deployment and monitoring through CI/CD pipeline (Docker, Kubernetes, or similar).
5. Experience with data and ML engineering infrastructure and tooling, including data processing runtimes and distributed systems, non-/relational databases, machine learning frameworks and services, and orchestration.
6. Work experience with a high level of test automation (unit, component, integration, E2E) and passion for developing clean, well maintainable, and testable code.
7. Motivation for continued personal development in discovering new technologies and software services.
8. Ability and eagerness to understand the business context where the team operates and the customer problems being solved.
9. Good communication skills to translate (even complex) analytical / engineering decisions and outcomes to broader, non-technical audience.

If you think you have what it takes, we encourage you to apply even if you don’t meet every single requirement.

OUR OFFER

Zalando provides a range of benefits, here’s an overview of what you can expect:

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

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