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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** Wallapop - **Location:** Barcelona, Spain (Remote available) - **Salary:** €25,000.0 - €60,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, Big Data, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, DevOps, Python (Programming Language), Machine Learning, Software Tools, Tensorflow, Azure Machine Learning, Search Technologies, Software Engineering, Pytorch, Large Language Models, Apache Spark, Indexer, Git, Pandas, Scikit Learn, Kubernetes, Low Latency, Apache Kafka, Machine Learning Operations, Software Coding - **Published:** July 21, 2026 - **Apply:** https://www.adzuna.es/contact-us.html ## About the Role Proven experience building and owning production-ready ML platforms and pipelines. You understand the full lifecycle from experimentation to monitoring. Deep 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 and Spanish, with the ability to explain complex technical concepts 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., Expertise Interview - run by the core team, focusing on the hard skills and the ability to deliver in a given context. This usually takes 60-90 minutes. ## Description 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 a Senior ML Engineer, you will lead the evolution of our ML Platform and MLOps practice. You will partner with Data Scientists, Data Engineers, and DevOps to shape 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 define 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. Define 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., Technical Task - you will be assigned a challenge to assess the technical skills required for the role., Stakeholder Interview - run by the hiring team and relevant stakeholders, focus on the ability to collaborate & deliver in a cross-functional set-up. This usually takes 60 minutes. Culture-Add Interview - run by culture interviewers, focus on adherence to Wallapop's purpose and business proposition. This usually takes 60 minutes. Offer - should you be the right candidate, your offer will be discussed over a call with talent acquisition and will then be confirmed in writing. 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