🛠 Tech Stack

💼 About This Role

You'll lead the evolution of Wallapop's ML Platform and MLOps practice, partnering with data scientists and engineers to scale models for millions of users. You'll drive end-to-end model lifecycle improvements and shape the long-term MLOps roadmap.

🎯 What You'll Do

• Maintain and improve ML platform for speed, reliability, and maintainability.
• Collaborate with data scientists to develop, deploy, and monitor scalable models.
• Promote engineering best practices like coding standards, testing, and CI/CD.
• Evaluate and integrate new tools for LLMs or real-time inference.
• Align ML development with company-wide data governance and infrastructure standards.

📋 Requirements

• Proven experience building production-ready ML platforms and pipelines.
• Deep understanding of AWS (SageMaker, Lambda, S3) and Kubernetes.
• Strong proficiency in Python, Git, and CI/CD workflows.
• Experience with real-time ML architectures using tools like Kafka.
• Hands-on experience with vector databases or semantic search (OpenSearch, Vertex AI).

✨ Nice to Have

• Experience with LLMs and RAG architectures (LangChain, LlamaIndex).
• Familiarity with Big Data technologies (Spark, Beam).
• Experience with other cloud platforms (GCP, Azure).

🎁 Benefits & Perks

• 📚 €2k Learning budget per year.
• 🍽️ Free office meals and lunch selection.
• 🏥 Private Health Insurance with Alan.
• 🏋️ Gym & wellness plan with physiotherapist.
• ✈️ 26 holidays per year.

📨 Hiring Process

Intro call, technical task, expertise interview, stakeholder interview, culture-add interview, then offer.