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

TheWhiteam; Tres Cantos; Presencial; EUR 52.582 - 56.088; Jornada completa

Descripción de la vacante

TheWhiteam is seeking a Data Science & MLOps Engineer to join the Advanced Analytics & AI team in Madrid. This role focuses on designing, developing, and deploying scalable machine learning and Generative AI solutions within an Azure-based ecosystem.

The ideal candidate will have 6–8 years of experience, strong proficiency in Python and MLOps, and expertise in building ML pipelines. On-site work is required with competitive compensation of 285–304 €/day.

Formación

• 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.
• Strong knowledge of data preprocessing, feature engineering, and model optimization.
• Experience with Git and collaborative development practices.
• English (C1) required.

Responsabilidades

• Design, develop, and deploy machine learning and Generative AI models.
• Build and maintain end-to-end ML pipelines.
• Collaborate with data scientists, engineers, and analysts.
• Implement and manage MLOps best practices.
• Optimize models for performance and scalability.
• Work with MLflow, Azure Machine Learning, and Azure DevOps.
• Drive innovation using emerging technologies.
• Communicate complex concepts to non-technical stakeholders.
• Participate in Agile/Scrum teams.

Conocimientos

Machine Learning Engineering

MLOps

Python (OOP)

PySpark

Scikit-learn

TensorFlow

PyTorch

Azure Cloud

Databricks

Git

English (C1)

Educación

Graduate level education

Herramientas

MLflow

Azure Machine Learning

Azure DevOps

Descripción del empleo

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.