Machine Learning Engineer, Search And Ranking Systems

Farfetch is a leading global marketplace for the luxury fashion industry. The Farfetch Marketplace connects customers in over 190 countries and territories with items from more than 50 countries and over 1,400 of the world's best brands, boutiques, and department stores, delivering a truly unique shopping experience and access to the most extensive selection of luxury on a global marketplace.

Our office is near Porto, in the north of Portugal, and is located in a vibrant business hub. It offers a dynamic and welcoming environment where our employees can connect and network with a large community of tech professionals.

We're on a mission to build end-to-end products and technology that powers the incredible e-commerce experience for luxury customers everywhere, understanding the motivations and needs of our customers and partners, to designing and testing hypotheses, to creating industry-leading experiences for luxury customers.

We're looking for a highly skilled Machine Learning Engineer to join our Search and Ranking team, a core function at the heart of our e-commerce platform. Our mission is to connect customers with the perfect products by delivering a fast, relevant, and personalized search experience. You will be at the forefront of this effort, tackling the unique challenges of search in the luxury fashion space, from understanding nuanced queries to ranking thousands of products accurately.

You will be instrumental in designing, building, and scaling our next generation of search and ranking systems, leveraging a powerful tech stack that includes advanced retrieval models and multimodal models.

You will work within a dynamic, interdisciplinary team of software engineers, data scientists, and machine learning engineers to product ionize cutting‑edge research and directly influence the technical direction of our platform. If you are passionate about building robust, scalable AI systems that solve complex, real‑world problems, this role is for you.

• Design, build, and deploy robust, end-to-end MLOps pipelines on Databricks for complex models, including NLP and multimodal systems.
• Architect and manage large-scale data flows using PySpark, pulling from diverse sources like Azure Data Lake Storage (ADLS) and Google Big Query to fuel our model training and inference services.
• Develop and maintain scalable APIs and services that can handle millions of requests daily to serve model predictions, ensuring high availability and low latency.
• Champion engineering best practices by writing clean, tested, and maintainable code, and developing reusable libraries and frameworks that accelerate the team's delivery.
• Implement comprehensive monitoring and alerting for model performance and data drift to ensure our systems remain accurate and reliable over time.

• A skilled software engineer with a passion for machine learning. You have proven experience building and deploying end-to-end ML‑powered products in a production environment.
• Proficient in Python and modern software engineering practices, including version control (Git), CI/CD, dependency management, and automated testing.
• Experienced with distributed data processing. You have hands‑on experience writing and optimizing complex data pipelines using Spark/PySpark.
• Comfortable in a cloud‑native environment. You have practical experience with a major cloud platform (Azure, GCP, or AWS) and its data services.
• An excellent collaborator and communicator, able to work effectively in a cross‑functional team of technical and non‑technical members.
• Nice to have:
• Deep expertise with the Databricks platform, including Delta Lake, MLflow, and model serving.
• Experience with containerization technologies like Docker and orchestration with Kubernetes.
• Experience with Redis, particularly in high‑throughput caching or as a low‑latency feature store.
• Experience with Apache Airflow or similar workflow orchestration tools for managing complex data and machine learning pipelines.
• Experience with monitoring and logging frameworks (Grafana, Prometheus).

• Health insurance for the whole family, flexible working environment and…