Data Science cum MLOps, Madrid (on-site) – International Client
Job role: Data Science cum MLOps.
Minimum experience: 6 to 8 years.
Studies required: Graduate.
Language: English (C1) (Mandatory).
Location: Madrid (on-site).
DESCRIPTION:
We are looking for a Data Science & MLOps Engineer to join our Advanced Analytics & AI team. This role focuses on designing, developing, and deploying scalable machine learning and Generative AI solutions within an Azure-based ecosystem.
You will collaborate with data scientists, data engineers, and business stakeholders to deliver end-to-end ML pipelines and production-ready AI models. The role requires a strong balance between data science expertise and MLOps practices, ensuring robust, scalable, and maintainable solutions.
The position involves working in Agile/DevOps environments and contributing to innovation initiatives that leverage emerging technologies such as GenAI and cloud platforms (Databricks, Azure).
Tasks:
· Design, develop, and deploy machine learning and Generative AI models for advanced analytics use cases.




· Build and maintain end-to-end ML pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.
· Collaborate closely with data scientists, data engineers, and analysts to deliver scalable AI solutions.
· Implement and manage MLOps best practices, ensuring model reproducibility, monitoring, and lifecycle management.
· Optimize models for performance and scalability in production environments.
· Work with tools such as MLflow, Azure Machine Learning, and Azure DevOps for pipeline orchestration and CI/CD.
· Drive innovation by expanding AI use cases using emerging technologies such as Generative AI.
· Communicate complex analytical concepts to non-technical stakeholders and guide decision-making.
· Participate in Agile/Scrum teams, contributing to continuous delivery and iterative product development.
· Stay updated on industry trends in AI, MLOps, cloud computing, and

📌 Data Science cum MLOps, Madrid (Tres Cantos)
🏢 The White Team
📍 Tres Cantos