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About the Role
We are tackling challenging problems in machine learning to build personalization systems that understand fashion and turn that understanding into reliable, scalable customer experiences. Your work will directly influence shopping journeys and customer communications, both online and in-store. This is a senior engineering role with technical ownership, defining how machine learning models move from experimentation into production, making architectural decisions, and building scalable systems.
Responsibilities
- Own the design, implementation, deployment, and evolution of production machine learning systems.
- Design architectures that serve models efficiently under real-world constraints, including large data volumes, reliability, and latency requirements.
- Build and operate ML systems across hybrid infrastructure, spanning cloud environments and on-premise data centers.
- Partner closely with Data Scientists to turn experiments and models into robust production capabilities while enabling rapid iteration.
- Make pragmatic technical decisions around model serving, data flows, observability, testing, and maintainability.
- Raise engineering standards for ML systems through strong system design, high code quality, and clear technical direction.
- Apply modern ML tools and approaches where they create measurable value.
- Work independently on ambiguous, technically challenging problems while helping others make progress.
Requirements
- Strong experience building production-grade software and taking ownership of systems beyond the prototype stage.
- Hands-on experience implementing and deploying machine learning solutions in production.
- Strong Python and SQL skills.
- Experience using Spark or comparable large-scale data processing technologies.
- A solid understanding of software architecture, APIs and services, testing, monitoring, and reliable production operations.
- The ability to evaluate trade-offs between model quality, latency, scalability, complexity, and maintainability.
- The confidence to make technical decisions independently, communicate them clearly, and collaborate closely with Data Scientists and Engineers.
- Tenacity, curiosity, and the ability to quickly learn and apply new technologies and approaches.
- Experience with recommender systems, personalization, ranking, or real-time machine learning.
- Experience with computer vision, multimodal ML, or deriving product understanding from image and catalog data.
- Experience designing or operating scalable model-serving infrastructure or ML platform components.
- A track record of mentoring engineers and improving engineering practices across a team.
Skills
- Python
- SQL
- Spark
- Machine Learning
- Personalization Systems
- Software Architecture
- APIs
- Services
- Testing
- Monitoring
- Production Operations
- Recommender Systems
- Ranking
- Real-time Machine Learning
- Computer Vision
- Multimodal ML
Location
- Remote
- Hybrid
Work Type
- Fully remote
- Hybrid working model
Experience Level
- Senior
Education Level
- BSc in Computer Science or related field, or equivalent practical knowledge and professional experience.
Benefits
- Flexible Ways of Working
- Opportunity to work remotely from another EU country for up to two weeks per year (for EU passport holders)
- Professional development support
About the Company
- We are ambitious in what we do, while maintaining a collaborative, down-to-earth, and supportive culture.
- We value strong engineering judgment, curiosity, pragmatism, and a willingness to learn and share knowledge.
- Join a company where your ideas matter.
- We value initiative and empower our people to help shape the business, influence how we work, and contribute to the future of our organization.
- From day one, you'll be trusted with meaningful responsibilities, encouraged to drive innovation, and supported in your professional development while working alongside experienced and passionate colleagues.