Experteer Overview
In this role you apply digital, data, ML and AI to real-world operations in Pharma Technical Operations. You will build and operate end-to-end ML pipelines, from data prep to model deployment and monitoring, partnering with data scientists, engineers and stakeholders. You help scale reliable, compliant ML solutions across manufacturing, quality, and supply chain. This is a hands-on, production-focused opportunity at Roche to move prototypes into production and continuously improve ML systems.
Compensaciones / Ventajas
• Build and maintain ML pipelines (data ingestion, preprocessing, feature generation, model training support, validation, packaging, deployment)
• Support deployment of ML models into cloud, hybrid, or application environments
• Contribute to model serving components and integration patterns
• Use experiment tracking and documentation to enable reproducibility and model comparison
• Contribute to data science–driven evaluation frameworks and benchmarks
• Develop reusable ML evaluation harnesses for testing across versions
• Monitor deployed models (performance, data quality, drift, latency, reliability)
• Provide production support and drive continuous improvement of ML systems
Responsabilidades
• Strong Python skills and software engineering practices
• Experience with Git, APIs, testing, documentation, collaborative development
• Exposure to ML workflows (data prep, feature engineering, model training, evaluation, deployment, monitoring)
• Experience with MLOps tools such as MLflow, model registries, experiment tracking, CI/CD, Docker, automated testing, monitoring
• Experience with SQL and data pipelines
• Exposure to cloud, preferably AWS, and containerized deployment
• Ability to work in cross-functional teams and communicate clearly
• Interest in building production-grade ML systems in regulated environments
• Experience in industrial/pharma/manufacturing/quality/supply chain environments is a plus
Requisitos principales
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📌 Machine Learning Engineer (Madrid)
🏢 Roche
📍 Madrid