Experteer Overview Solicitar este puesto es sencillo. Desplácese hacia abajo y haga clic en "Solicitar" para ser considerado para esta posición. In this role you drive quality assurance for cutting-edge AI/ML digital solutions in a GMP environment at Roche. You will partner with data scientists, software and IT teams to validate and operate AI/ML systems that support GMP objectives. You mitigate quality, security, and data privacy risks across the AI/ML lifecycle while aligning validation strategies with general regulatory frameworks. You'll influence stakeholders across units and foster capability in digital validation, contributing to Roche's mission to improve patient care. Compensaciones / Beneficios
* Lead QA oversight, validation, and compliant execution of AI/ML systems in a regulated GMP environment
* Collaborate with data science, software development, and IT to integrate AI/ML into business applications under CSV/CSA frameworks
* Create and approve validation documents (validation plans, specs, architecture, test scripts)
* Identify and mitigate quality, security,



and data privacy risks across the AI/ML lifecycle
* Align diverse stakeholders to establish compliant validation strategies for digital solutions
* Drive continuous improvement of CSV/CSA processes and integrate AI risk management into quality systems
* Mentor colleagues in digital compliance and validation practices Responsabilidades
* BS/MS in science, CS, engineering, or related field
* 5–7 years in a regulated pharma/biotech/medical xcskxlj device environment
* Hands-on experience designing/validating/implementing AI/ML systems in commercial settings
* Knowledge of FDA/EMA regulations, GAMP5, 21 CFR Part 11, Annex 11, ICH Q9/Q10
* Programming skills (Python, R) and cloud platforms (AWS, Azure, GCP) with MLOps for production governance
* Strong analytical, problem-solving, and communication skills
* Ability to work cross-functionally and influence stakeholders Requisitos principales •

📌 AI/ML Compliance Lead (Madrid)
🏢 Confidential
📍 Madrid