Führt Teams bei Software- und ML-Systemen zur Zahlungsrisiko- und Betrugserkennung, verantwortet Architektur und begleitet Produktivsetzung und Incident-Reviews.
About : We are seeking a MLOps Engineer (m/f/d) to build, operate, and improve ML/AI solutions in production.
The Lounge Assortment Optimisation team builds the decision products behind a better assortment and customer experience.
Wir schreiben dir, sobald eine neue geprüfte Stelle zu MLOps dazukommt. Höchstens eine Nachricht am Tag, und nur, wenn es tatsächlich etwas Neues gibt.
Abmelden mit einem Klick, jederzeit. Keine Weitergabe an Dritte.
Warum dieser Job gelistet ist
Principal-Engineering-Rolle im Risikomanagement mit benannter ML- und MLOps-Anforderung; ML-Systeme sind Teil des Arbeitsergebnisses, die Kernrolle bleibt aber Softwarearchitektur und Führung.. Prüfverfahren ansehen
& THE TEAM In this role as Principal Software Engineer, you will guide multiple teams within the Risk Management department. This department focuses on developing Software and Machine Learning solutions to manage risk and detect fraud in payment transactions amounting to billions of euros annually. These systems are crucial to Zalando s financial success by identifying, managing, and mitigating payment risks.
You will be responsible for elevating architectural and software engineering standards, mentoring engineers, and leading groundbreaking initiatives. As a key member of the leadership team, you will collaborate closely with Engineering Managers, Applied Science Managers, other Principal Software Engineers, Principal Applied Scientists, and Product Managers. If you are enthusiastic about software, Machine Learning, architecture, and driving business impact, we encourage you to apply.
INCLUSIVE BY DESIGN If you think you have what it takes, we encourage you to apply even if you don t meet every single requirement. You may just be the right candidate for this or other roles! At Zalando, our vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce – one that thrives on diversity and is truly inclusive by design.
We believe that diverse teams fuel innovation and creativity, and we actively seek out talent from all backgrounds. We actively seek to reduce bias in our hiring and employment processes, focusing on your qualifications, skills, and contributions. To support this, we kindly ask that you refrain from including personal details such as your photo, age, or marital status in your CV, ensuring a fair and equitable evaluation based solely on your abilities and potential.
We are committed to providing an exceptional and accessible candidate experience for everyone. If you require any accommodations to support you throughout the hiring process, please let us know – we are here to assist you. Discover more about our commitment to creating a diverse and inclusive workplace: WHAT WE’D LOVE YOU TO DO (AND LOVE DOING) - You’ll design and drive technical solution design for high impact ambiguous projects developed by multiple teams. - You ll break down complex solutions into iterations to reduce risk and complexity, and ship large scale projects to production by driving, mentoring, designing and code contributions. - You ll evangelize good software practices based on your experience and industry established patterns.
You’ll drive technical innovation in the department or across teams. - You ll provide technical guidance and mentorship to software engineers on their day to day work. - You ll contribute to improving the operational excellence of the systems owned by the department by driving operational review meetings and post mortems of incidents. You’ll drive or provide hands-on support for time critical investigation on anomalies. - You ll establish yourself as a sparring partner for the tech and product leadership teams on both tech and product topics. You’ll researche and propose solutions to improve productivity and effectiveness using technical knowledge and expertise.
WE’D LOVE TO MEET YOU IF - 3+ years of experience as a Principal Engineer, Solutions Architect or Staff Engineer - You have extensive experience in software architecture and design in cloud environments, with a strong track record of leading complex projects spanning multiple teams and departments. - You have experience with Machine Learning, especially around productionzing and MLOps. - You demonstrate strong leadership and communication skills to effectively guide and mentor teams through architectural decisions and project implementations. - You are not afraid to get hands-on, even though you excel at delegation. 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. - 27 days of holiday a year to start for full-time employees - 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 - Employee shares program - 40% off fashion and beauty products sold and shipped by Zalando, 30% off Lounge by Zalando, discounts from external partners - 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 peer-to-peer review Learn all about Zalando and our values here:
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Die vollständige Anzeige und das Bewerbungsformular liegen beim Arbeitgeber.
Zur OriginalanzeigeMLOps ist die Antwort auf ein verbreitetes Problem: Ein Modell funktioniert im Notizbuch und nie im Betrieb. Diese Rollen kümmern sich um alles dazwischen, um Trainingsläufe, die sich wiederholen lassen, um Versionen von Daten und Modellen, um Überwachung im laufenden Betrieb und um den Weg einer Änderung bis zur Auslieferung. Verlangt werden häufig Container, eine Cloud-Umgebung und Werkzeuge wie MLflow oder Kubeflow. Wer aus dem klassischen Systembetrieb kommt, hat hier gute Aussichten, auch ohne je selbst ein Modell trainiert zu haben.