ph3Job Overview /h3 pData Science MLOps Engineer to join the Advanced Analytics AI team. Focus on designing, developing, and deploying scalable machine learning and Generative AI solutions within an Azure-based ecosystem. /p h3Responsibilities /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 h3Qualifications /h3 ul li6–8 years of experience in Machine Learning Engineering or Applied ML with strong exposure to MLOps. /li liAdvanced proficiency in Python (OOP) and PySpark. /li liHands‑on experience with Scikit‑learn, TensorFlow, or PyTorch. /li liStrong experience with Azure Cloud and Databricks. /li liExpertise in building ML pipelines using MLflow, Azure ML, and CI/CD tools (Azure DevOps). /li liStrong knowledge of data preprocessing, feature engineering, model optimization, and evaluation techniques (cross‑validation, A/B testing). /li liExperience with Git and collaborative development practices. /li liGraduate level education. /li liEnglish (C1) required. /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 h3Location Compensation /h3 pMadrid (on site). 285–304 €/day. /p /p #J-18808-Ljbffr

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