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You will be updated with latest job alerts via emailINCLUSIVE BY DESIGN
At Zalando our vision is to be the leading panEuropean ecosystem for fashion and lifestyle ecommerce 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. We only want to know why youre great for this role so please avoid including your picture age and marital status in your CV as well.
We want to provide you with a great candidate experience. Please feel free to inform us of any accommodations you may need so we can best support and assist you throughout the hiring process.
our diversity & inclusion strategy: ROLE AND THE TEAM
At Zalando our vision is to be the Starting Point for Fashion. We want to offer a shopping experience that is characterized by trust for our more than 50 million customers in 25 markets across Europe and also for our 6500 partner brands. To maintain this trust it is vital for us to manage transactional risks that originate from suspicious behaviors on our fashion platform. With 3.3 million shopping items resulting in hundreds of thousands of orders every single day we use big data and advanced methods from machine learning to predict and mitigate such risks and ensure trustful relationships with our customers and partners.
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 a machine learning team we are responsible for several predictive services running in Java Python AWS and Kubernetes to safeguard teams across Zalando. 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 you build and put in production is impacting not only every single Zalando customer on the spot but also the business performance of Zalando and its partners.
WHAT WED LOVE YOU TO DO (AND LOVE DOING)
We are looking for a passionate and proactive senior engineer that has proficiency in both the data and machine learning domain. You will participate in the full development life cycle endtoend from design implementation and testing to documentation delivery support and maintenance. Contribute to our growing engineering and science community and encourage knowledge sharing in an agile work environment.
Data Engineering:
Implement operate and continuously improve largescale data pipelines for batch and realtime processing to enable risk inference and risk assessment
Increase the operational excellence of our data pipelines by using best practices for data quality assurance testing monitoring alerting and cost efficiency
Support the development of a feature store consisting of features for risk inference and risk assessment
Own the design development and maintenance of ongoing metrics reports analyses and dashboards to drive key business decisions
ML Engineering:
Deploy operate and continuously improve our largescale machine learning services for detecting transactional risks including batch and realtime inference on cloudbased infrastructure
Responsible for teams endtoend MLOps productionizing machine learning services including workflow automation and orchestration
Tackle challenges for developing algorithms and running them efficiently on cloudbased infrastructure
Increase operational excellence of our machine learning services by introducing best practices for model testing experimentation versioning serving retraining monitoring and alerting
WED LOVE TO MEET YOU IF
5 years of handson experience as a software engineer data engineer or machine learning engineer that productionized and operated data pipelines machine learning models for largescale services in cloud environments (preferably AWS)
Proficiency in Python SQL (expertise in Java and Scala is preferred)
Experience in designing developing and operating highlyscalable microservices (API design) on a distributed system
Knowledge in automated deployment and monitoring through CI/CD pipeline (Docker Kubernetes or similar)
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
Work experience with a high level of test automation (unit component integration E2E) and passion for developing clean well maintainable and testable code
Motivation for continued personal development in discovering new technologies and software services
Ability and eagerness to understand the business context where the team operates and the customer problems being solved
Good communication skills to translate (even complex) analytical / engineering decisions and outcomes to broader nontechnical audience
If you think you have what it takes we encourage you to apply even if you dont meet every single requirement. You may just be the right candidate for this or other roles!
OUR OFFER
Zalando provides a range of benefits heres an overview of what you can expect. Ask your Talent Acquisition Partner to learn more about what we offer.
Employee shares program
40 off fashion and beauty products sold and shipped by Zalando 30 off Lounge by Zalando discounts from external partners
2 paid volunteering days a year
Hybrid working model with up to 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 to start for fulltime employees
Relocation assistance available (subject to prior agreement)
Family services including counseling and support
Health and wellbeing options (including Wellhub formerly Gympass)
Mental health support and coaching available
Drive your development through our training platform and biannual peertopeer review
Required Experience:
Senior IC
Full-Time