• Establecer pipelines CI/CD para modelos de IA • Definir estándares de versionado y deployment de modelos • Crear sistemas de monitorización y alertas • Implementar protocolos de rollback y A/B testing • Automatizar procesos de entrenamiento y validación

• Design, develop, and deploy scalable AI/ML models for document processing and automation. • Build end-to-end pipelines for data extraction, classification, and validation. • Implement and integrate Document AI and OCR-based solutions. • Develop LLM-driven applications using modern frameworks and orchestration tools. • Collaborate with cross-functional teams to deliver business-focused AI solutions. • Optimize model performance, accuracy, and scalability in production environments. • Stay updated with the latest advancements in AI/ML technologies.

• Design, build, and maintain robust ETL pipelines to support AI model development and deployment. • Develop, train, and optimize machine learning models used in radiotherapy software. • Collaborate with product and research teams to bring new AI-driven features and algorithms into production. • Support FDA submissions by contributing to documentation, validation, and regulatory processes. • Participate in design reviews, risk analyses, and cross-functional discussions to ensure safe and effective products. • Mentor junior engineers and data scientists and contribute to a collaborative team environment.

• Design, build, evaluate, and ship LLM-based solutions that give users more adaptive control over their listening experience • Work on prompted playlist experiences with a focus on music fulfillment and session generation • Collaborate with cross-functional partners across user research, design, data science, product, and engineering • Prototype new ML approaches and bring them into production at global scale • Build and improve systems that connect artists and fans in personalized and meaningful ways • Contribute to the development of scalable ML systems serving hundreds of millions of users • Promote best practices in ML system design, testing, evaluation, and deployment across the organization • Actively contribute to a strong community of machine learning practitioners at Spotify