Top Machine Learning Jobs in Portugal

Own and scale half-hourly forecasting models for frontline workforce demand, lead end-to-end client launches (data validation, model selection, UAT, monitoring), join client calls, build stakeholder relationships, and maintain production ML systems that handle messy data and feedback loops.

The AI/ML Engineer will design and deploy AI pipelines, integrating LLMs into production, and develop scalable machine learning systems while collaborating with stakeholders and data engineers.

Responsible for building, deploying, and maintaining scalable machine learning solutions, implementing end-to-end ML pipelines, and ensuring model production quality.

Responsible for building, deploying, and maintaining scalable machine learning solutions, ensuring the transition from prototypes to production. Duties include designing ML pipelines, managing automated CI/CD processes, fine-tuning model performance, and collaborating with Data Scientists.

The role involves developing scalable AI solutions, optimizing pipelines, mentoring engineers, and collaborating in a cross-functional team to enhance data insights for life sciences.

Lead the design and implementation of scalable AI and ML solutions. Collaborate with teams to develop architecture and MLOps best practices, ensuring AI governance and operational excellence.

The ML Ops Engineer will build and operate scalable ML inference platforms, focusing on model serving infrastructure and deployment pipelines for AI applications.

The Principal AI/ML Scientist & Engineer will lead a team, focusing on AI/ML strategy and developing data products for business outcomes.

The intern will develop AI models, enhance neural mechanism understanding, and collaborate on generative modeling while maintaining code quality.

Train and evaluate machine learning models, build predictive models, design feature pipelines, and integrate models into production systems.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.