Senior ML Ops Engineer (all genders)

ABOUT THE TEAM
Department: Lounge by Zalando
Reports to: Julius Monello
Team Size: 7
Recruiter Name: Benan Ababay
THE ROLE AND THE TEAM
Lounge by Zalando is an online shopping club for fashion and lifestyle products across Europe. At the core of our high-growth strategy is pricing and assortment optimization. As a shopping club, Lounge's main premise is to offer exclusive deals with limited availability to fashion conscious customers. 
As a Senior ML Ops Engineer on the Pricing Algorithms team, you will contribute and shape the development of the core components of the article lifecycle optimization platform, following engineering best practices with a strong focus on operational excellence and high reliability. Developing a world-class pricing algorithm is a great opportunity to directly contribute to a key pillar of Lounge’s future success: Machine learning, econometrics, and operations research drive our efforts to optimise ca. 5 billion EUR in discount investments each year.  

INCLUSIVE BY DESIGN
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

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)
Develop and support automate and scalable data, ML, and optimization pipelines, ensuring data integrity and reliability.
Contribute to develop the full ML lifecycle for different kinds of ML and optimisation models. Further support our rigorous online AB-testing of all our algorithmic improvements.
Contribute to the definition of best practices and set up proper tooling to support them, such as continuous integration/delivery, code/data quality, test coverage, etc.
Build analytical and operational offline testing pipelines & dashboards to further enhance the ability of our  team and stakeholders to make data driven decisions.

WE’D LOVE TO MEET YOU IF
You have 3+ years of work experience building and operating Data, Optimization and/or Machine Learning pipelines.
You have strong programming skills in Python and are proficient with modern software engineering practices
You have experience in ML Ops and Machine Learning and know that the answer to how to build a better model isn’t always “more parameters” 
Solid relational database skills and SQL language. Experience with ETL/ELT tools like dbt, Airflow, data warehouses or data lakes is a big plus

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.

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 to start

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

Drive your development through our training platform and biannual peer-to-peer review

Learn all about Zalando and our values here: https://jobs.zalando.com/en/?gh_src=22377bdd1us 
Please note that all applications must be completed using the online form - we do not accept applications via email.