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On-siteFull-timeMid levelProductVisa sponsorship
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Wallapop is a Barcelona based scale-up driven by the purpose to empower people to embrace a more conscious and human way of consumption. We believe in a world where collaborative economy is mainstream. This is what drives us. 💫
Wallapop operates in Spain, Italy and Portugal, offering a catalogue of several hundreds of millions of products and services. Powered by technical innovation and continuous improvement, we bring together the scale & trust of classifieds with the marketplace’s convenience & reach. 🌱 Our mission is to enable a connected trade ecosystem, making 2nd-hand the norm through smart use of technology.
The Challenge 🧩
Wallapop generates billions of data points daily. With a mature data infrastructure already in place, our Data Science and Machine Learning area is gaining significant momentum. As we scale, we face the exciting challenge of taking our ML Platform to the next level to support complex solutions in Personalization, Search, Trust & Safety, and Logistics. As an ML Engineer (MLOps), you will contribute to the evolution of our ML Platform and MLOps practice. You will partner with Data Scientists, Data Engineers, and DevOps to collaborate on a vision that balances innovation with reliability, ensuring our models scale efficiently to serve millions of users.
What You Will Do 👇
Iterate and maintain Wallapop’s ML Platform, identifying opportunities to improve speed, reliability, and maintainability. You will help execute the long-term vision and roadmap for MLOps.
Work hand-in-hand with Data Scientists to support their efforts, ensuring they have the tooling to develop, deploy, and monitor scalable models efficiently.
Adopt and promote engineering best practices (coding standards, testing, CI/CD) within the ML domain.
Partner with Data Engineering and DevOps to align ML development with company-wide infrastructure and data governance standards.
Investigate and integrate new frameworks and tools (e.g., for LLMs or real-time inference) to keep our stack modern and effective.
What We’re Looking For 🔎
Solid experience contributing to and maintaining production-ready ML platforms and pipelines. You understand the lifecycle from experimentation to monitoring.
Solid understanding of AWS components (SageMaker, Lambda, S3) and container orchestration with Kubernetes.
Strong software engineering background with proficiency in Python, Git, and CI/CD workflows. You write robust, testable code.
Experience with real-time ML architectures, leveraging tools like Kafka for low-latency ingestion and inference.
Hands-on experience with vector databases or semantic search infrastructure (e.g., OpenSearch, Vertex AI), including indexing and retrieval tuning.
Familiarity with the broader ML toolkit, such as orchestration/tracking tools (Flyte, MLFlow, Feast) and standard libraries (Pandas, Scikit-learn, TensorFlow/PyTorch).
Professional proficiency in English, with the ability to communicate technical concepts clearly to diverse stakeholders.
What Would Be A Plus 🚀
Hands-on experience working with LLMs, RAG architectures, and libraries like LangChain or LlamaIndex.
Familiarity with Big Data technologies like Spark or Beam.
Experience with Data Engineering tools such as Airflow, dbt, or Datahub.
Experience with other cloud platforms like GCP or Azure in addition to AWS.
Do note that all our jobs are 📍 Barcelona based. We follow a hybrid model where flexibility rules. We commit to a minimum of 6 days per month in the office. Each team self-organizes to decide on cadence and in-person/remote rituals.
Wallapop is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees as we want Wallapop to be a place for everyone.
Additionally to the opportunity to contribute to an agile product set up and work together towards achieving our meaningful mission, we offer the following 🍭 Perks & Benefits:
What does the hiring process for this position look like? 👀 **Please, note that all interviews take place remotely over hangouts.**