ph3Data Science cum MLOps, Madrid (on-site) – International Client /h3 pbJob role: /b Data Science cum MLOps. /p pbMinimum experience: /b 6 to 8 years. /p pbStudies required: /b Graduate. /p pbLanguage: /b English (C1) (Mandatory). /p pbLocation: /b Madrid (on-site). /p h3DESCRIPTION /h3 pWe 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. /p pYou 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. /p pThe position involves working in Agile/DevOps environments and contributing to innovation initiatives that leverage emerging technologies such as GenAI and cloud platforms (Databricks, Azure). /p h3Tasks /h3 ul liDesign, develop, and deploy machine learning and Generative AI models for advanced analytics use cases. /li liBuild and maintain end-to-end ML pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment. /li liCollaborate closely with data scientists, data engineers, and analysts to deliver scalable AI solutions. /li liImplement and manage MLOps best practices, ensuring model reproducibility, monitoring, and lifecycle management. /li liOptimize models for performance and scalability in production environments. /li liWork with tools such as MLflow, Azure Machine Learning,



and Azure DevOps for pipeline orchestration and CI/CD. /li liDrive innovation by expanding AI use cases using emerging technologies such as Generative AI. /li liCommunicate complex analytical concepts to non-technical stakeholders and guide decision-making. /li liParticipate in Agile/Scrum teams, contributing to continuous delivery and iterative product development. /li liStay updated on industry trends in AI, MLOps, cloud computing, and data platforms. /li /ul h3Specific Expertise /h3 ul liExperience: 6–8 years in Machine Learning Engineering or Applied ML, with strong exposure to MLOps. /li liProgramming: Advanced proficiency in Python (OOP) and PySpark. /li liML Frameworks: Hands-on experience with Scikit-learn, TensorFlow, or PyTorch. /li liCloud Platforms: Strong experience with Azure Cloud and Databricks. /li liMLOps Pipelines: Expertise in building ML pipelines using MLflow, Azure ML, and CI/CD tools (Azure DevOps). /li liData Modeling: Strong knowledge of data preprocessing, feature engineering, model optimization, and evaluation techniques (cross-validation, A/B testing). /li liVersion Control: Experience with Git and collaborative development practices. /li /ul h3Nice to Have /h3 ul liKnowledge of Generative AI frameworks (e.g., LangChain). /li liFamiliarity with vector databases. /li liExperience with model monitoring and logging in production. /li liUnderstanding of data governance and compliance. /li liRelevant Databricks or Azure certifications. /li /ul h3Language /h3 ul liEnglish (C1). /li /ul h3Location /h3 pMadrid (on site). /p h3Rate /h3 p285-304 €/day. /p /p #J-18808-Ljbffr

📌 Data Science cum MLOps, Madrid (on-site) – International Client (Tres Cantos)
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📍 Tres Cantos