ML Engineer - Hybrid Barcelona, Personalization & AI

Aristocrat Leisure Ltd.; Bellprat; Hybride; EUR 55 000 - 90 000; Plein temps

Avantages offerts par ce poste

Hybrid work model

Barcelona office 3 days per week

Résumé du poste

Aristocrat Leisure Ltd. in Barcelona is hiring an ML Engineer to build and deploy machine learning and AI solutions that enhance personalized player experiences and business outcomes.

You will collaborate with data scientists and software engineers to develop scalable ML components and AI workflows. The role emphasizes Python development, model evaluation, MLOps collaboration, and data integration from multiple sources.

Qualifications

• 2+ years of professional experience in software engineering, machine learning engineering, or AI development.
• Strong Python programming skills with experience in building and testing ML models.
• Hands-on experience with ML frameworks such as PyTorch or TensorFlow and with evaluating model performance.

Responsabilités

• Develop ML models for prediction, recommendation, and personalization.
• Build AI applications including LLM-powered workflows and RAG components.
• Create ML/AI components, APIs, and services to integrate into existing apps.
• Collaborate with data scientists, engineers, and product teams to deliver practical ML/AI solutions.
• Support production deployment with monitoring and lifecycle management.

Connaissances

Python programming

Team collaboration

Problem solving

Communication

Formation

Bachelor's/Master's/PhD in CS/ML/AI or related field

Outils

TensorFlow

PyTorch

scikit-learn

SQL

CI/CD pipelines

Description du poste

Aristocrat Leisure Ltd. in Barcelona is hiring an ML Engineer to build and deploy machine learning and AI solutions that enhance personalized player experiences and business outcomes.

You will collaborate with data scientists and software engineers to develop scalable ML components and AI workflows. The role emphasizes Python development, model evaluation, MLOps collaboration, and data integration from multiple sources.