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.

#J-18808-Ljbffr

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