Job Overview Data 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.

Responsibilities

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.

Qualifications

6–8 years of experience in Machine Learning Engineering or Applied ML with strong exposure to MLOps.

Advanced proficiency in Python (OOP) and PySpark.

Hands‑on experience with Scikit‑learn, TensorFlow, or PyTorch.

Strong experience with Azure Cloud and Databricks.

Expertise in building ML pipelines using MLflow, Azure ML, and CI/CD tools (Azure DevOps).

Strong knowledge of data preprocessing, feature engineering, model optimization, and evaluation techniques (cross‑validation, A/B testing).

Experience with Git and collaborative development practices.

Graduate level education.

English (C1) required.

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.

Location & Compensation Madrid (on site). 285–304 €/day.

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