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

La oferta

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.