Machine Learning Engineer

About the role

Alongside, a Portuguese company that partners with international organizations to build and scale tech teams, is recruiting a Machine Learning Engineer for a client project. The client is a global leader in professional information solutions and software, operating in more than 180 countries and serving Healthcare, Tax & Accounting, Financial & Corporate Compliance and Legal & Regulatory sectors.

Key responsibilities

• Design, develop and maintain scalable data and end-to-end ML pipelines, from data ingestion to production deployment.
• Build and deploy ML services and APIs, ensuring reliability, scalability and performance.
• Partner with Data Scientists to turn models into robust, production-ready solutions.
• Implement MLOps best practices, including CI/CD, testing, data and code quality, monitoring and model lifecycle management.
• Troubleshoot production ML systems and drive technical and architectural decisions.
• Work with AWS ML services, especially SageMaker, and containerized environments with Docker and Kubernetes.
• Contribute to GenAI implementations within the platform framework.
• Mentor team members and deliver in an Agile/Scrum environment.

Required profile

• Degree in Computer Engineering, IT or a related field.
• 5+ years of experience in Backend Engineering and/or Machine Learning Engineering.
• Fluent English and strong communication and technical decision-making skills.

Required skills

• Strong production-level Python development.
• Hands-on experience building E2E ML pipelines and deploying models via APIs.
• SQL/NoSQL databases, testing frameworks and data/code quality practices.
• MLOps tools such as MLflow, Kubeflow or similar.
• Strong AWS knowledge, especially SageMaker, and Docker and Kubernetes.
• Nice to have: Computer Vision, NLP, TensorFlow/PyTorch, Scikit-Learn, Pandas, Terraform/CloudFormation, asynchronous messaging and ML observability tools.

What we offer

• Hybrid model: 2 days per week in the office in Porto.
• Collaborative, international work environment.
• Impactful software products and transformation projects, exposure to modern technologies and collaboration with professionals across countries.