AI Engineer: Cloud Data & ML Pipelines (Hybrid)

Capgemini Engineering; Porto; Híbrido; EUR 50.000 - 80.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work

Health insurance

Life insurance

Career growth

Training programs

International projects

Descripción de la vacante

Capgemini Engineering is seeking an experienced AI Engineer in Porto, Portugal to design, develop, and deploy scalable data and AI platforms in cloud environments. You will collaborate with multidisciplinary teams to transform business requirements into production-ready systems, focusing on data pipelines, ML models, and cloud-native architectures on GCP.

The ideal candidate has a strong background in Data Science/ML/Data Engineering with Python, SQL, and data modeling skills, plus English

Formación

• Experience in Data Science, ML Engineering or Data Engineering.
• Strong Python and SQL with data modeling.
• Experience building data pipelines and processing workflows.
• English fluency and ability to collaborate across teams.

Responsabilidades

• Design, develop, and maintain scalable data and AI solutions.
• Build data pipelines supporting analytics and ML use cases.
• Train, deploy, and monitor ML models in production.
• Collaborate with data scientists, engineers, architects, and stakeholders.
• Implement cloud-native AI/data architectures, preferably on Google Cloud Platform (GCP).
• Ensure data quality, governance, security, and performance across data platforms.
• Automate data processing, model deployment, and monitoring through CI/CD and MLOps.

Conocimientos

Python

SQL

Data Science

Machine Learning

Google Cloud

Educación

Bachelor's or Master's in CS/DS/Engineering

Herramientas

CI/CD

MLOps

Descripción del empleo

Capgemini Engineering is seeking an experienced AI Engineer in Porto, Portugal to design, develop, and deploy scalable data and AI platforms in cloud environments. You will collaborate with multidisciplinary teams to transform business requirements into production-ready systems, focusing on data pipelines, ML models, and cloud-native architectures on GCP.

The ideal candidate has a strong background in Data Science/ML/Data Engineering with Python, SQL, and data modeling skills, plus English