Principal Engineer - Discovery (All Genders)
THE ROLE & THE TEAM
As a Principal Engineer in the Discovery team you will work with exceptional engineers and science leaders and can spearhead the strategy on building platform capabilities and ML infrastructure, collaborate closely with the Discovery teams and the central Machine learning productivity teams.
We are looking for a Principal Engineer with experience with ML systems to be part of the Discovery team to define and drive the develop platform capabilities, to collaborate closely with applied scientists, and the wider PRSB organization.
WHERE YOUR EXPERTISE IS NEEDED
- Mentor junior to senior engineers and actively collaborate with other teams. Share knowledge and expertise within our talented engineering and science community.
- Architect, design and develop our machine learning platform capabilities and infrastructure to be able to serve our 51M customers.
- Work closely with applied science and engineering leaders, product managers and other business stakeholders to bring our state-of-the-art solutions to the customers and to discover and identify new opportunities.
- Drive the operationalization of solutions deployed in production, and help the team grow and cultivate best practices in software development and MLOps. Operate a complex and advanced system landscape that meets the highest standards in terms of reliability, performance, and latency.
WHAT WE’RE LOOKING FOR
- 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).
- Experience leading the architecture and design (design patterns, reliability and scaling) and building of new and current machine learning systems.
- Expert in Python, Scala and Spark. Hands-on experience with Docker, Git, AWS EC2, S3, Databricks, SageMaker, Flink, PostgreSQL, Redis, or other RDBMS. Experience in working with ML products, especially deep learning applications around natural language processing, computer vision, and information retrieval, and deployment of LLMs. Experience with deep learning frameworks (e.g. TensorFlow, PyTorch, etc.) is a plus.
- 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. Experience serving large language models is a plus.
- Good communication skills and experience leading organization-wide collaborations. Ability and eagerness to understand the business context where the team operates and the customer problems being solved.
- Experience coaching and mentoring senior engineers, and working closely with applied scientists, senior machine learning engineers and data scientists.
Zalando Benefits
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
- 1 paid volunteering days a year
- Hybrid working model with 60% (or more) 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 (for Zalando SE)
- 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
ABOUT ZALANDO
It’s the perfect time to join Zalando on our journey, from being a pioneer in the world of e-commerce, to the starting point for fashion in Europe. We connect customers, brands, and partners across 25 markets.
Help us drive digital and sustainable solutions for fashion, logistics, advertising and research, bringing head-to-toe fashion to more than 50 million active customers through a team of diverse skill-sets, cultural backgrounds, and interests.
Please note that all applications must be completed using the online form - we do not accept applications via email.
