Data Science cum MLOps, Madrid (on-site) – International Client

**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 platforms. **Specific Expertise:** * Experience: 6–8 years in Machine Learning Engineering or Applied ML, with strong exposure to MLOps. * Programming: Advanced proficiency in Python (OOP) and PySpark. * ML Frameworks: Hands-on experience with Scikit-learn, TensorFlow, or PyTorch. * Cloud \& Platforms: Strong experience with Azure Cloud and Databricks. * MLOps \& Pipelines: Expertise in building ML pipelines using MLflow, Azure ML, and CI/CD tools (Azure DevOps). * Data \& Modeling: Strong knowledge of data preprocessing, feature engineering, model optimization, and evaluation techniques (cross-validation, A/B testing). * Version Control: Experience with Git and collaborative development practices. **Nice to Have:** * Knowledge of Generative AI frameworks (e.g., LangChain). * Familiarity with vector databases. * Experience with model monitoring and logging in production. * Understanding of data governance and compliance. * Relevant Databricks or Azure certifications. **Language:** * English (C1\). **Location:** * Madrid (on site). **Rate:** * 285-304 €/day.