MLOps Engineer

Responsibilities

• ▹Iterate and maintain Wallapop's ML Platform, identifying opportunities to improve speed, reliability, and maintainability
• ▹Help execute the long-term vision and roadmap for MLOps
• ▹Work hand-in-hand with Data Scientists, 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 the stack modern and effective

Requirements

• ▹Solid experience contributing to and maintaining production-ready ML platforms and pipelines, understanding 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
• ▹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

Nice to have

• ▹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

About the company

Wallapop is a Barcelona-based scale-up driven by the purpose to empower people to embrace a more conscious and human way of consumption. It generates billions of data points daily, with a mature data infrastructure, and its Data Science and ML area is gaining significant momentum across Personalization, Search, Trust & Safety, and Logistics.