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As a Principal Machine Learning Engineer in ZMS, you will be the tech lead working with other ML engineers to build our real-time recommendation engine for our Ad Tech platform which includes organic and multimedia ads. This position is a unique opportunity to have visible impact, and connect with exceptional talents from many different backgrounds: you will be part of a cross-functional team of Applied Scientists, Data Engineers and Software Engineers. Together, and with the support of Product Managers and Designers, you create, design and deliver new features to serve our customers and partners needs.
Job Responsibility:
Drive the operationalization of solutions deployed in production, and help the team grow and cultivate best practices in software development and MLOps
Architect and lead the development of machine learning solutions that can handle low latency, high availability and high volume scenarios
Mentor engineers and provide technical guidance across multiple projects simultaneously while managing competing priorities effectively within agreed-upon timelines
Apply techniques and create processes to optimise deployed models for better performance, latency, and memory usage
Work closely with applied science and engineering teams, product managers and other business stakeholders to bring our state-of-the-art solutions to customers and to discover and identify new opportunities
Requirements:
Excellent software development engineering skills to design computationally effective solutions for machine learning operationalization and maintenance (MLOps/MLaaS) in large-scale production environments (data engineering, data version control, model serving, continuous monitoring & alerting)
Strong verbal and written communication and presentation abilities when discussing complex ideas with both technical and non-technical stakeholders alike
Hands-on professional experience in programming, using Python, Java Flink, pySpark, PyTorch, and TensorFlow
Strong programming skills with a high performance language (Java, Scala, Go, etc) and experience working with Python in production
Experience building, deploying and operating data-driven systems in a cloud environment, including experience with feature stores & feature engineering pipelines, data ingestion & transformation, machine learning workflow orchestration
Thrive to coach and mentor senior engineers, and work closely with applied scientists, senior machine learning engineers and data scientists
What we offer:
27 days of holiday a year to start for full-time employees (+1 day for every calendar year up to 30 days)
2 paid volunteering days a year
Hybrid working model with up to 60% remote per week
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